Publications · Gregory Dudek

431 publications

AMP2026: A Multi-Platform Marine Robotics Dataset for Tracking and Mapping
E. Meriaux; S. Wen; D. Widhalm; Z. Wang; J. Shi; M. Sosa Guzm\'an; K. Jakkala; B. A. Carley; E. Sokolova; Y. Girdhar; M. Roznere; J. M. O'Kane; J. Sattar; G. Dudek

2026arXiv preprint arXiv …
Abstract
Abstract
Marine environments present significant challenges for perception and autonomy due to dynamic surfaces, limited visibility, and complex interactions between aerial, surface, and submerged sensing modalities. This paper introduces the Aerial Marine Perception Dataset (AMP2026), a multi-platform marine robotics dataset collected across multiple field deployments designed to support research in two primary areas: multi-view tracking and marine environment mapping. The dataset includes synchronized data from aerial drones
Topics
aerial roboticsenvironment mappinglocalizationslamunderwater robotics
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@misc{amp2026amultiplatformmarineroboticsdatas, author = {E. Meriaux and S. Wen and D. Widhalm and Z. Wang and J. Shi and M. Sosa Guzm\'an and K. Jakkala and B. A. Carley and E. Sokolova and Y. Girdhar and M. Roznere and J. M. O'Kane and J. Sattar and G. Dudek}, title = {AMP2026: A Multi-Platform Marine Robotics Dataset for Tracking and Mapping}, year = {2026}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2603.04225}, }
Contractive Diffusion Policies
A. Soleimani Abyaneh; C. Morissette; M. H. Danesh; A. Houssaini; D. Meger; G. Dudek

2026International Conference on Learning Representations
Abstract
Abstract
Diffusion policies have emerged as powerful generative models for offline policy learning, whose sampling process can be rigorously characterized by a score function guiding a Stochastic Differential Equation (SDE). However, the same score-based SDE modeling that grants diffusion policies the flexibility to learn diverse behavior also incurs solver and score-matching errors, large data requirements, and inconsistencies in action generation. While less critical in image generation, these inaccuracies compound and lead to failure in
Topics
behavior cloninggenerative aireinforcement learningvariational methods
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@misc{contractivediffusionpolicies2026, author = {A. Soleimani Abyaneh and C. Morissette and M. H. Danesh and A. Houssaini and D. Meger and G. Dudek}, title = {Contractive Diffusion Policies}, year = {2026}, booktitle = {International Conference on Learning Representations}, url = {https://proceedings.iclr.cc/paper_files/paper/2026/hash/1dec73169509c223220744b2c9b2df37-Abstract-Conference.html}, }
Do LLMs Beat Nash? Testing Decentralized Coordination in Self-Play Multi-Agent Games
D Sinishaw; Q Zhu; E Meriaux; G Dudek

2026arXiv preprint arXiv:2608.12547
Abstract
Abstract
Large language model agents deployed without a central controller are often assumed to require communication to coordinate their actions. We ask what remains possible without it: when independent instances of the same model cannot communicate, can they still reason about their counterparts well enough to exceed the standard game-theoretic baseline for uncoordinated play? We introduce a benchmark of one-shot, no-communication games in which each of thirteen language models is told only that its counterparts are running the
Topics
generative ai
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@misc{dollmsbeatnashtestingdecentralizedcoordi, author = {D Sinishaw and Q Zhu and E Meriaux and G Dudek}, title = {Do LLMs Beat Nash? Testing Decentralized Coordination in Self-Play Multi-Agent Games}, year = {2026}, journal = {arXiv preprint arXiv:2608.12547}, url = {https://arxiv.org/abs/2608.12547}, }
MANSION: Multi-floor lANguage-to-3D Scene generatIOn for loNg-horizon tasks
L. Che; S. Wen; S. Huang; C. Wang; Y. Yang; G. Dudek; X. Wang; J. Su

2026arXiv preprint arXiv …
Abstract
Abstract
Real-world robotic tasks are long-horizon and often span multiple floors, demanding rich spatial reasoning. However, existing embodied benchmarks are largely confined to single-floor in-house environments, failing to reflect the complexity of real-world tasks. We introduce MANSION, the first language-driven framework for generating building-scale, multi-floor 3D environments. Being aware of vertical structural constraints, MANSION generates realistic, navigable whole-building structures with diverse, human-friendly scenes, enabling
Topics
generative ai
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@misc{mansionmultifloorlanguageto3dscenegenera, author = {L. Che and S. Wen and S. Huang and C. Wang and Y. Yang and G. Dudek and X. Wang and J. Su}, title = {MANSION: Multi-floor lANguage-to-3D Scene generatIOn for loNg-horizon tasks}, year = {2026}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2603.11554}, }
On the Coverage of Planar Worlds with Simulated Mobile Ad Hoc Networks
E. Meriaux; S. Wen; L.-R. Langevin; A. Loria; G. Dudek

20262026
Abstract
Abstract
On the Coverage of Planar Worlds with Simulated Mobile Ad Hoc Networks
Topics
complexity boundstelecommunications
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@misc{onthecoverageofplanarworldswithsimulated, author = {E. Meriaux and S. Wen and L.-R. Langevin and A. Loria and G. Dudek}, title = {On the Coverage of Planar Worlds with Simulated Mobile Ad Hoc Networks}, year = {2026}, journal = {2026}, }
Tactile modality fusion for vision-language-action models
C. Morissette; A. Abyaneh; W.-D. Chang; A. Houssaini; D. Meger; H.-C. Lin; G. Dudek

2026European Conference on Computer Vision
Abstract
Abstract
We propose TacFiLM, a lightweight modality-fusion approach, integrates visual-tactile signals into vision-language-action (VLA) models. Advances in VLAs have introduced robot policies that are generalizable and semantically grounded, primarily relying on vision-based perception. However, vision alone cannot capture complex interaction dynamics during contact-rich manipulation like contact forces, surface friction, compliance, and shear. While recent attempts to integrate tactile signals into VLA models add complexity through token
Topics
generative aitactile sensing
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@misc{tactilemodalityfusionforvisionlanguageac, author = {C. Morissette and A. Abyaneh and W.-D. Chang and A. Houssaini and D. Meger and H.-C. Lin and G. Dudek}, title = {Tactile modality fusion for vision-language-action models}, year = {2026}, booktitle = {European Conference on Computer Vision}, url = {https://link.springer.com/chapter/10.1007/978-3-032-37092-1_2}, }
The surprising difficulty of search in model-based reinforcement learning
W.-D. Chang; M. Henaff; B. Amos; G. Dudek; S. Fujimoto

2026arXiv preprint arXiv …
Abstract
Abstract
This paper investigates search in model-based reinforcement learning (RL). Conventional wisdom holds that long-term predictions and compounding errors are the primary obstacles for model-based RL. We challenge this view, showing that search is not a drop-in replacement for a learned policy. Surprisingly, we find that search can harm performance even when the model is highly accurate. Instead, we show that mitigating overestimation bias matters more than improving model or value function accuracy. Building on this insight
Topics
reinforcement learning
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@misc{thesurprisingdifficultyofsearchinmodelba, author = {W.-D. Chang and M. Henaff and B. Amos and G. Dudek and S. Fujimoto}, title = {The surprising difficulty of search in model-based reinforcement learning}, year = {2026}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2601.21306}, }
A Blockchain Framework for Equitable and Secure Task Allocation in Robot Swarms
H. Zhao; A. Pacheco; G. Beltrame; X. Liu; M. Dorigo; G. Dudek

20252026 IEEE International Conference on Robotics and Automation (ICRA), Vienna, Austria
Abstract
Abstract
Recent studies demonstrate the potential of blockchain to enable robots in a swarm to achieve secure consensus about the environment, particularly when robots are homogeneous and perform identical tasks. Typically, robots receive rewards for their contributions to consensus achievement, but no studies have yet targeted heterogeneous swarms, in which the robots have distinct physical capabilities suited to different tasks. We present a novel framework that leverages domain knowledge to decompose the swarm
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@misc{ablockchainframeworkforequitableandsecur, author = {H. Zhao and A. Pacheco and G. Beltrame and X. Liu and M. Dorigo and G. Dudek}, title = {A Blockchain Framework for Equitable and Secure Task Allocation in Robot Swarms}, year = {2025}, booktitle = {2026 IEEE International Conference on Robotics and Automation (ICRA), Vienna, Austria}, url = {https://ieeexplore.ieee.org/abstract/document/11150749/}, }
A Blockchain Framework for Equitable and Secure Task Allocation in Robot Swarms
H. Zhao; A. Pacheco; G. Beltrame; X. Liu; M. Dorigo; G. Dudek

20252026 IEEE International Conference on Robotics and Automation (ICRA), Vienna, Austria
Abstract
Abstract
Recent studies demonstrate the potential of blockchain to enable robots in a swarm to achieve secure consensus about the environment, particularly when robots are homogeneous and perform identical tasks. Typically, robots receive rewards for their contributions to consensus achievement, but no studies have yet targeted heterogeneous swarms, in which the robots have distinct physical capabilities suited to different tasks. We present a novel framework that leverages domain knowledge to decompose the swarm
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@misc{ablockchainframeworkforequitableandsecur, author = {H. Zhao and A. Pacheco and G. Beltrame and X. Liu and M. Dorigo and G. Dudek}, title = {A Blockchain Framework for Equitable and Secure Task Allocation in Robot Swarms}, year = {2025}, booktitle = {2026 IEEE International Conference on Robotics and Automation (ICRA), Vienna, Austria}, url = {https://ieeexplore.ieee.org/abstract/document/11150749/}, }
Decentralized Multi-Agent Goal Assignment for Path Planning using Large Language Models
M. Ismayilov; E. Meriaux; S. Wen; G. Dudek

20252025 IEEE MIT Undergraduate Research Technology Conference (URTC)
Abstract
Abstract
Coordinating multiple autonomous agents in shared environments under decentralized conditions is a long-standing challenge in robotics and artificial intelligence. This work addresses the problem of decentralized goal assignment for multiagent path planning, where agents independently generate ranked preferences over goals based on structured representations of the environment, including grid visualizations and scenario data. After this reasoning phase, agents exchange their goal rankings, and assignments are determined by
Topics
generative aipath planning
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@misc{decentralizedmultiagentgoalassignmentfor, author = {M. Ismayilov and E. Meriaux and S. Wen and G. Dudek}, title = {Decentralized Multi-Agent Goal Assignment for Path Planning using Large Language Models}, year = {2025}, booktitle = {2025 IEEE MIT Undergraduate Research Technology Conference (URTC)}, url = {https://ieeexplore.ieee.org/abstract/document/11532975/}, }
Generalizable imitation learning through pre-trained representations
W. -D. Chang; F. Hogan; S. Fujimoto; D. Meger; G. Dudek

2025… on Robotics and …
Abstract
Abstract
In this paper, we leverage self-supervised vision transformer models and their emergent semantic abilities to improve the generalization abilities of imitation learning policies. We introduce DVK, an imitation learning algorithm that leverages rich pre-trained Visual Transformer patch-level embeddings to obtain better generalization when learning through demonstrations. Our learner sees the world by clustering appearance features into groups associated with semantic concepts, forming stable keypoints that generalize across a wide
Topics
behavior cloningdeep learningobject recognition
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@misc{generalizableimitationlearningthroughpre, author = {W. -D. Chang and F. Hogan and S. Fujimoto and D. Meger and G. Dudek}, title = {Generalizable imitation learning through pre-trained representations}, year = {2025}, journal = {… on Robotics and …}, url = {https://ieeexplore.ieee.org/abstract/document/11127800/}, }
Large Pre-Trained Models for Bimanual Manipulation in 3D
H. Yurchyk; W.-D. Chang; G. Dudek; D. Meger

20252025 IEEE-RAS 24th International Conference on Humanoid Robots (Humanoids)
Abstract
Abstract
We investigate the integration of attention maps from a pre-trained Vision Transformer into voxel representations to enhance bimanual robotic manipulation. Specifically, we extract attention maps from DINOv2, a self-supervised ViT model, and interpret them as pixel-level saliency scores over RGB images. These maps are lifted into a 3D voxel grid, resulting in voxel-level semantic cues that are incorporated into a behavior cloning policy. When integrated into a state-of-theart voxel-based policy, our attention-guided featurization yields
Topics
behavior cloningdeep learning
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@misc{largepretrainedmodelsforbimanualmanipula, author = {H. Yurchyk and W.-D. Chang and G. Dudek and D. Meger}, title = {Large Pre-Trained Models for Bimanual Manipulation in 3D}, year = {2025}, booktitle = {2025 IEEE-RAS 24th International Conference on Humanoid Robots (Humanoids)}, url = {https://ieeexplore.ieee.org/abstract/document/11203079/}, }
Learning active tactile perception through belief-space control
Tremblay; Meger; Hogan; Dudek] Jean-FranÃ§ois Tremblay; David Meger; Francois R Hogan; Gregory Dudek.

20252025 IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Robots operating in an open world will encounter novel objects with unknown physical properties, such as mass, friction, or size. These robots will need to sense these properties through interaction prior to performing downstream tasks with the objects. We propose a method that autonomously learns tactile exploration policies by developing a generative world model that is leveraged to 1) estimate the object's physical parameters using a differentiable Bayesian filtering algorithm and 2) develop an exploration policy using an
Topics
adaptive controlbayesian inferencegenerative aitactile sensing
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@misc{learningactivetactileperceptionthroughbe, author = {Tremblay and Meger and Hogan and Dudek] Jean-FranÃ§ois Tremblay and David Meger and Francois R Hogan and Gregory Dudek.}, title = {Learning active tactile perception through belief-space control}, year = {2025}, booktitle = {2025 IEEE International Conference on Robotics and Automation (ICRA)}, url = {https://ieeexplore.ieee.org/abstract/document/11127425/}, }
Learning heuristics for transit network design and improvement with deep reinforcement learning
A. Holliday; A. El-Geneidy; G. Dudek

2025Transportmetrica B: Transport Dynamics, vol. 13, no. 1, article 2561863, 2025
Abstract
Abstract
Learning heuristics for transit network design and improvement with deep reinforcement learning
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@misc{learningheuristicsfortransitnetworkdesig, author = {A. Holliday and A. El-Geneidy and G. Dudek}, title = {Learning heuristics for transit network design and improvement with deep reinforcement learning}, year = {2025}, journal = {Transportmetrica B: Transport Dynamics, vol. 13, no. 1, article 2561863, 2025}, }
On Mobile Ad Hoc Networks for Coverage of Partially Observable Worlds
E. Meriaux; S. Wen; L.-R. Langevin; D. Precup; A. Lor\'ia; G. Dudek

2025arXiv preprint arXiv …
Abstract
Abstract
This paper addresses the movement and placement of mobile agents to establish a communication network in initially unknown environments. We cast the problem in a computational-geometric framework by relating the coverage problem and line-of-sight constraints to the Cooperative Guard Art Gallery Problem, and introduce its partially observable variant, the Partially Observable Cooperative Guard Art Gallery Problem (POCGAGP). We then present two algorithms that solve POCGAGP: CADENCE, a
Topics
complexity bounds
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@misc{onmobileadhocnetworksforcoverageofpartia, author = {E. Meriaux and S. Wen and L.-R. Langevin and D. Precup and A. Lor\'ia and G. Dudek}, title = {On Mobile Ad Hoc Networks for Coverage of Partially Observable Worlds}, year = {2025}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2512.09495}, }
Scalable Aerial GNSS Localization for Marine Robots
S. Wen; E. Meriaux; M. Sosa Guzm\'an; C. Morissette; C. Si; B. Baghi; G. Dudek

2025arXiv preprint arXiv …
Abstract
Abstract
Accurate localization is crucial for water robotics, yet traditional onboard Global Navigation Satellite System (GNSS) approaches are difficult or ineffective due to signal reflection on the water's surface and its high cost of aquatic GNSS receivers. Existing approaches, such as inertial navigation, Doppler Velocity Loggers (DVL), SLAM, and acoustic-based methods, face challenges like error accumulation and high computational complexity. Therefore, a more efficient and scalable solution remains necessary. This paper proposes an alternative
Topics
aerial roboticslocalizationsonar and acousticsunderwater navigationunderwater robotics
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@misc{scalableaerialgnsslocalizationformariner, author = {S. Wen and E. Meriaux and M. Sosa Guzm\'an and C. Morissette and C. Si and B. Baghi and G. Dudek}, title = {Scalable Aerial GNSS Localization for Marine Robots}, year = {2025}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2505.04095}, }
Stable Multi-Drone GNSS Tracking System for Marine Robots
S. Wen; E. Meriaux; M. Sosa Guzm\'an; Z. Wang; J. Shi; G. Dudek

2025arXiv preprint arXiv …
Abstract
Abstract
Accurate localization is essential for marine robotics, yet Global Navigation Satellite System (GNSS) signals are unreliable or unavailable even at a very short distance below the water surface. Traditional alternatives, such as inertial navigation, Doppler Velocity Loggers (DVL), SLAM, and acoustic methods, suffer from error accumulation, high computational demands, or infrastructure dependence. In this work, we present a scalable multi-drone GNSS-based tracking system for surface and near-surface marine robots. Our approach combines efficient
Topics
aerial roboticscooperative localizationlocalizationsonar and acousticsunderwater robotics
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@misc{stablemultidronegnsstrackingsystemformar, author = {S. Wen and E. Meriaux and M. Sosa Guzm\'an and Z. Wang and J. Shi and G. Dudek}, title = {Stable Multi-Drone GNSS Tracking System for Marine Robots}, year = {2025}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2511.18694}, }
Stable Multi-Drone GNSS Tracking System for Marine Robots
S. Wen; E. Meriaux; M. Sosa Guzm\'an; Z. Wang; J. Shi; G. Dudek

2025arXiv preprint arXiv …
Abstract
Abstract
Accurate localization is essential for marine robotics, yet Global Navigation Satellite System (GNSS) signals are unreliable or unavailable even at a very short distance below the water surface. Traditional alternatives, such as inertial navigation, Doppler Velocity Loggers (DVL), SLAM, and acoustic methods, suffer from error accumulation, high computational demands, or infrastructure dependence. In this work, we present a scalable multi-drone GNSS-based tracking system for surface and near-surface marine robots. Our approach combines efficient
Topics
aerial roboticscooperative localizationlocalizationsonar and acousticsunderwater robotics
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@misc{stablemultidronegnsstrackingsystemformar, author = {S. Wen and E. Meriaux and M. Sosa Guzm\'an and Z. Wang and J. Shi and G. Dudek}, title = {Stable Multi-Drone GNSS Tracking System for Marine Robots}, year = {2025}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2511.18694}, }

Swarm Oracle: Trustless Blockchain Agreements through Robot Swarms

A. Pacheco; H. Zhao; V. Strobel; T. Roukny; G. Dudek; A. Reina; M. Dorigo

2025arXiv preprint arXiv:2509.15956, 2025

Abstract

Swarm Oracle: Trustless Blockchain Agreements through Robot Swarms

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@misc{swarmoracletrustlessblockchainagreements,
  author = {A. Pacheco and H. Zhao and V. Strobel and T. Roukny and G. Dudek and A. Reina and M. Dorigo},
  title = {Swarm Oracle: Trustless Blockchain Agreements through Robot Swarms},
  year = {2025},
  journal = {arXiv preprint arXiv:2509.15956, 2025},
}

Visual-Tactile Inference of 2.5 D Object Shape from Marker Texture
A. Jilani; F. Hogan; C. Morissette; G. Dudek; M. Jenkin; K. Siddiqi

2025IEEE Robotics and Automation Letters
Abstract
Abstract
Visual-tactile sensing affords abundant capabilities for contact-rich object manipulation tasks including grasping and placing. Here we introduce a shape-from-texture inspired contact shape estimation approach for visual-tactile sensors equipped with visually distinct membrane markers. Under a perspective projection camera model, measurements related to the change in marker separation upon contact are used to recover surface shape. Our approach allows for shape sensing in real time, without requiring network training or
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@article{Jilani2025, author = {A. Jilani and F. Hogan and C. Morissette and G. Dudek and M. Jenkin and K. Siddiqi}, title = {Visual-Tactile Inference of 2.5 D Object Shape from Marker Texture}, journal = {IEEE Robotics and Automation Letters}, volume = {10}, number = {2}, pages = {1042--1049}, year = {2025} }
A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object tracking
Lotfi; F.; K. Virji; N. Dudek; G. Dudek

2024Proc Intelligent Robotics and Systems
Abstract
Abstract
In this paper, we present an exploration and assessment of employing a centralized deep Q-network (DQN) controller as a substitute for the prevalent use of PID controllers in the context of 6DOF swimming robots. Our primary focus centers on illustrating this transition with the specific case of underwater object tracking. DQN offers advantages such as data efficiency and off-policy learning, while remaining simpler to implement than other reinforcement learning methods. Given the absence of a dynamic model for our robot, we
Topics
adaptive controlreinforcement learningunderwater robotics
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@inproceedings{Lotfi2024, author = {Lotfi, F. and Virji, K. and Dudek, N. and Dudek, G.}, title = {A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object tracking}, booktitle = {Proc Intelligent Robotics and Systems}, year = {2024}, note = {To appear}, url = {http://arxiv.org/abs/2401.16618}, eprint = {2401.16618}, archivePrefix = {arXiv}, primaryClass = {cs.RO}, month = {Jan}, year = {2024}, note = {Accessed: Apr. 11, 2024} }
A Neural-Evolutionary Algorithm for Autonomous Transit Network Design
Holliday; A.; G. Dudek

2024Proc. International Conference on Robotics and Automation
Abstract
Abstract
Planning a public transit network is a challenging optimization problem, but essential in order to realize the benefits of autonomous buses. We propose a novel algorithm for planning networks of routes for autonomous buses. We first train a graph neural net model as a policy for constructing route networks, and then use the policy as one of several mutation operators in a evolutionary algorithm. We evaluate this algorithm on a standard set of benchmarks for transit network design, and find that it outperforms the learned policy
Topics
complexity boundsreinforcement learning
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@inproceedings{Holliday2024, author = {A. Holliday and G. Dudek}, title = {A Neural-Evolutionary Algorithm for Autonomous Transit Network Design}, booktitle = {Proc. International Conference on Robotics and Automation}, year = {2024}, month = {May}, url = {http://arxiv.org/abs/2403.07917} }
Accelerating digital twin calibration with warm-start Bayesian optimization
Abhisek Konar; Amal Feriani; Di Wu; Seowoo Jang; Xue Liu; Gregory Dudek.

2024ICC 2024-IEEE …
Abstract
Abstract
Digital twins are expected to play an important role in the widespread adaptation of AI-based networking solutions in the real world. The calibration of these virtual replicas is critical to ensure a trustworthy replication of the real environment. This work focuses on the input parameter calibration of radio access network (RAN) simulators using real network performance metrics as supervision signals. Usually, the RAN digital twin is considered a black-box function and each calibration problem is viewed as a standalone search problem
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@misc{acceleratingdigitaltwincalibrationwithwa, author = {Abhisek Konar and Amal Feriani and Di Wu and Seowoo Jang and Xue Liu and Gregory Dudek.}, title = {Accelerating digital twin calibration with warm-start Bayesian optimization}, year = {2024}, journal = {ICC 2024-IEEE …}, url = {https://ieeexplore.ieee.org/abstract/document/10622967/}, }
Adaptive dynamic programming for energy-efficient base station cell switching
Luo; Junliang; Yi Tian Xu; Di Wu; Michael Jenkin; Xue Liu; Gregory Dudek.

20242024 IEEE International Conference on Communications Workshops (ICC Workshops)
Abstract
Abstract
Energy saving in wireless networks is growing in importance due to increasing demand for evolving new-gen cellular networks, environmental and regulatory concerns, and potential energy crises arising from geopolitical tensions. In this work, we propose an approximate dynamic programming (ADP)-based method coupled with online optimization to switch on/off the cells of base stations to reduce network power consumption while maintaining adequate Quality of Service (QoS) metrics. We use a multilayer perceptron (MLP) given
Topics
telecommunications
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@inproceedings{luo2024adaptive, title={Adaptive dynamic programming for energy-efficient base station cell switching}, author={Luo, Junliang and Xu, Yi Tian and Wu, Di and Jenkin, Michael and Liu, Xue and Dudek, Gregory}, booktitle={2024 IEEE International Conference on Communications Workshops (ICC Workshops)}, pages={1365--1370}, year={2024}, organization={IEEE} }
AIoT smart home via autonomous LLM agents
Rivkin; Hogan; Feriani; Konar; Sigal; Liu; Dudek] Dmitriy Rivkin; Francois Hogan; Amal Feriani; Abhisek Konar; Adam Sigal; Xue Liu; Gregory Dudek.

2024IEEE Internet of …
Abstract
Abstract
The common-sense reasoning abilities and vast general knowledge of large language models (LLMs) make them a natural fit for interpreting user requests in a smart home assistant context. LLMs, however, lack specific knowledge about the user and their home, which limits their potential impact. Smart home agent with grounded execution (SAGE), overcomes these and other limitations by using a scheme in which a user request triggers an LLM-controlled sequence of discrete actions. These actions can be used to retrieve
Topics
generative aitelecommunications
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@misc{aiotsmarthomeviaautonomousllmagents2024, author = {Rivkin and Hogan and Feriani and Konar and Sigal and Liu and Dudek] Dmitriy Rivkin and Francois Hogan and Amal Feriani and Abhisek Konar and Adam Sigal and Xue Liu and Gregory Dudek.}, title = {AIoT smart home via autonomous LLM agents}, year = {2024}, journal = {IEEE Internet of …}, url = {https://ieeexplore.ieee.org/abstract/document/10729865/}, }
Anomaly Detection for Scalable Task Grouping in Reinforcement Learning-based RAN Optimization
Li; Jimmy; Igor Kozlov; Di Wu; Xue Liu; Gregory Dudek.

20242024 IEEE International Conference on Communications Workshops (ICC Workshops)
Abstract
Abstract
The use of learning-based methods for optimizing cellular radio access networks (RAN) has received increasing attention in recent years. This coincides with a rapid increase in the number of cell sites worldwide, driven largely by dramatic growth in cellular network traffic. Training and maintaining learned models that work well across a large number of cell sites has thus become a pertinent problem. This paper proposes a scalable framework for constructing a reinforcement learning policy bank that can perform RAN optimization across
Topics
anomaly detectionreinforcement learningtelecommunications
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@inproceedings{li2024anomaly, title={Anomaly Detection for Scalable Task Grouping in Reinforcement Learning-based RAN Optimization}, author={Li, Jimmy and Kozlov, Igor and Wu, Di and Liu, Xue and Dudek, Gregory}, booktitle={2024 IEEE International Conference on Communications Workshops (ICC Workshops)}, pages={1395--1400}, year={2024}, organization={IEEE} }
CARTIER: Cartographic lAnguage Reasoning Targeted at Instruction Execution for Robots
Rivkin; Dmitriy; Kakodkar; Nikhil Rajiv; Hogan; Francois; Hamed Baghi; Bobak; Dudek; Gregory.

2024Proc. International Conference on Robotics and Automation
Abstract
Abstract
This work explores the capacity of large language models (LLMs) to address problems at the intersection of spatial planning and natural language interfaces for navigation. We focus on following complex instructions that are more akin to natural conversation than traditional explicit procedural directives typically seen in robotics. Unlike most prior work where navigation directives are provided as simple imperative commands (eg," go to the fridge"), we examine implicit directives obtained through conversational interactions. We leverage
Topics
complexity boundsgenerative aihuman-robot interactionlocalizationobject recognition
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@inproceedings{rivkin2024cartier, title={CARTIER: Cartographic lAnguage Reasoning Targeted at Instruction Execution for Robots}, author={Rivkin, Dmitriy and Kakodkar, Nikhil Rajiv and Hogan, Francois and Hamed Baghi, Bobak and Dudek, Gregory}, booktitle={Proc. International Conference on Robotics and Automation}, year={2024}, month={May} }
Computational principles of mobile robotics
G. Dudek; M. Jenkin; "

2024NA
Abstract
Abstract
Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary field of mobile robotics, which lies at the intersection of artificial intelligence, computational vision, and traditional robotics. Written for advanced undergraduates and graduate students in computer science and engineering, the book covers algorithms for a range of strategies for locomotion, sensing, and reasoning. The new edition includes recent advances in robotics and intelligent machines, including coverage of human-robot interaction, robot
Topics
localizationslam
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@misc{computationalprinciplesofmobilerobotics2, author = {G. Dudek and M. Jenkin and "}, title = {Computational principles of mobile robotics}, year = {2024}, journal = {NA}, url = {https://books.google.com/books?hl=en&lr=&id=Rc_3EAAAQBAJ&oi=fnd&pg=PP1&dq=+G.+Dudek+and+M.+Jenkin,+%22Computational+Principles+of+Mobile+Robotics,%22+3rd+ed.,+Cambridge+University+Press,+2024.&ots=VIED5KX5Ay&sig=v2MM1K3vi4Ds3mWC-WRk8juE7js}, }

Computational Principles of Mobile Robotics (3rd edition)

Dudek, Gregory; Jenkin, Michael

2024Cambridge University Press

Abstract

Computational Principles of Mobile Robotics 3rd edition

Topics

localizationslam

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@book{dudek2024computational,
  title={Computational Principles of Mobile Robotics (3rd edition)},
  author={Dudek, Gregory and Jenkin, Michael},
  edition={3rd},
  year={2024},
  publisher={Cambridge University Press},
  isbn={9780521692120},
  pages={450}
}

Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs

Lotfi; F.; F. Faraji; N. Kakodkar; T. Manderson; D. Meger; G. Dudek

2024arXiv preprint arXiv:2404.02294

Abstract

This paper explores leveraging large language models for map-free off-road navigation using generative AI, reducing the need for traditional data collection and annotation. We propose a method where a robot receives verbal instructions, converted to text through Whisper, and a large language model (LLM) model extracts landmarks, preferred terrains, and crucial adverbs translated into speed settings for constrained navigation. A language-driven semantic segmentation model generates text-based masks for identifying landmarks

Topics

generative ailandmark-based methods

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@article{lotfi2024constrained,
 abstract = {This paper explores leveraging large language models for map-free off-road navigation using generative AI, reducing the need for traditional data collection and annotation. We propose a method where a robot receives verbal instructions, converted to text through Whisper, and a large language model (LLM) model extracts landmarks, preferred terrains, and crucial adverbs translated into speed settings for constrained navigation. A language-driven semantic segmentation model generates text-based masks for identifying landmarks},
 author = {Lotfi, Faraz and Faraji, Farnoosh and Kakodkar, Nikhil and Manderson, Travis and Meger, David and Dudek, Gregory},
 journal = {arXiv preprint arXiv:2404.02294},
 pub_year = {2024},
 title = {Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs},
 venue = {arXiv preprint arXiv …}
}

Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs

Lotfi; F.; F. Faraji; N. Kakodkar; T. Manderson; D. Meger; G. Dudek

2024arXiv preprint arXiv:2404.02294

Abstract

Topics

generative ailandmark-based methods

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@article{lotfi2024constrained,
 abstract = {This paper explores leveraging large language models for map-free off-road navigation using generative AI, reducing the need for traditional data collection and annotation. We propose a method where a robot receives verbal instructions, converted to text through Whisper, and a large language model (LLM) model extracts landmarks, preferred terrains, and crucial adverbs translated into speed settings for constrained navigation. A language-driven semantic segmentation model generates text-based masks for identifying landmarks},
 author = {Lotfi, Faraz and Faraji, Farnoosh and Kakodkar, Nikhil and Manderson, Travis and Meger, David and Dudek, Gregory},
 journal = {arXiv preprint arXiv:2404.02294},
 pub_year = {2024},
 title = {Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs},
 venue = {arXiv preprint arXiv …}
}

Device-Free Human State Estimation Using UWB Multi-Static Radios
S. A. Laham; B. H. Baghi; P.-Y. Lajoie; A. Feriani; S. Herath; S. Liu; G. Dudek

2024arXiv preprint arXiv:2401.05410, 2024
Abstract
Abstract
Device-Free Human State Estimation Using UWB Multi-Static Radios
Topics
localization
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@misc{devicefreehumanstateestimationusinguwbmu, author = {S. A. Laham and B. H. Baghi and P.-Y. Lajoie and A. Feriani and S. Herath and S. Liu and G. Dudek}, title = {Device-Free Human State Estimation Using UWB Multi-Static Radios}, year = {2024}, journal = {arXiv preprint arXiv:2401.05410, 2024}, }
Hallucination detection and hallucination mitigation: An investigation
J Luo; T Li; D Wu; M Jenkin; S Liu; G Dudek

2024arXiv preprint arXiv …
Abstract
Abstract
Large language models (LLMs), including ChatGPT, Bard, and Llama, have achieved remarkable successes over the last two years in a range of different applications. In spite of these successes, there exist concerns that limit the wide application of LLMs. A key problem is the problem of hallucination. Hallucination refers to the fact that in addition to correct responses, LLMs can also generate seemingly correct but factually incorrect responses. This report aims to present a comprehensive review of the current literature on both hallucination
Topics
generative ai
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@misc{hallucinationdetectionandhallucinationmi, author = {J Luo and T Li and D Wu and M Jenkin and S Liu and G Dudek}, title = {Hallucination detection and hallucination mitigation: An investigation}, year = {2024}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2401.08358}, }
Imitation Learning from Observation through Optimal Transport
Chang, Wei-Di; Fujimoto, Scott; Meger, David; Dudek, Gregory

2024Proceedings of the Reinforcement Learning Conference (RLC)
Abstract
Abstract
Imitation Learning from Observation (ILfO) is a setting in which a learner tries to imitate the behavior of an expert, using only observational data and without the direct guidance of demonstrated actions. In this paper, we re-examine the use of optimal transport for IL, in which a reward is generated based on the Wasserstein distance between the state trajectories of the learner and expert. We show that existing methods can be simplified to generate a reward function without requiring learned models or adversarial learning. Unlike
Topics
reinforcement learningteleoperation
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@inproceedings{chang2024imitation, title={Imitation Learning from Observation through Optimal Transport}, author={Chang, Wei-Di and Fujimoto, Scott and Meger, David and Dudek, Gregory}, booktitle={Proceedings of the Reinforcement Learning Conference (RLC)}, year={2024}, note={to appear}, url={https://openreview.net/pdf?id=RI5frp6she} }
Interacting with a Visuotactile Countertop
Jenkin; Michael; Francois R. Hogan; Kaleem Siddiqi; Jean-Francois Tremblay; Bobak Baghi; Gregory Dudek.

2024International Conference on Robotics, Computer Vision and Intelligent Systems
Abstract
Abstract
We present the See-Through-your-Skin Display (STS-d), a device that integrates visual and tactile sensing with a surface display to provide an interactive user experience. The STS-d expands the application of visuo-tactile optical sensors to Human-Robot Interaction (HRI) tasks and Human-Computer Interaction (HCI) tasks more generally. A key finding of this paper is that it is possible to display graphics on the reflective membrane of semi-transparent optical tactile sensors without interfering with their sensing capabilities
Topics
human-robot interactiontactile sensing
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@inproceedings{Jenkin2024, author = {Michael Jenkin and Francois R. Hogan and Kaleem Siddiqi and Jean-François Tremblay and Bobak Baghi and Gregory Dudek}, title = {Interacting with a Visuotactile Countertop}, booktitle = {International Conference on Robotics, Computer Vision and Intelligent Systems}, pages = {361--374}, year = {2024}, publisher = {Springer Nature Switzerland}, address = {Cham} }
Multimodal and force-matched imitation learning with a see-through visuotactile sensor
Ablett; Limoyo; Sigal; Jilani; Kelly; Siddiqi; Hogan; Dudek] Trevor Ablett; Oliver Limoyo; Adam Sigal; Affan Jilani; Jonathan Kelly; Kaleem Siddiqi; Francois Hogan; Gregory Dudek.

2024IEEE Transactions …
Abstract
Abstract
Contact-rich tasks continue to present many challenges for robotic manipulation. In this work, we leverage a multimodal visuotactile sensor within the framework of imitation learning (IL) to perform contact-rich tasks that involve relative motion (eg, slipping and sliding) between the end-effector and the manipulated object. We introduce two algorithmic contributions, tactile force matching and learned mode switching, as complimentary methods for improving IL. Tactile force matching enhances kinesthetic teaching by reading
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@misc{multimodalandforcematchedimitationlearni, author = {Ablett and Limoyo and Sigal and Jilani and Kelly and Siddiqi and Hogan and Dudek] Trevor Ablett and Oliver Limoyo and Adam Sigal and Affan Jilani and Jonathan Kelly and Kaleem Siddiqi and Francois Hogan and Gregory Dudek.}, title = {Multimodal and force-matched imitation learning with a see-through visuotactile sensor}, year = {2024}, journal = {IEEE Transactions …}, url = {https://ieeexplore.ieee.org/abstract/document/10814647/}, }
Optimizing Energy Saving for Wireless Networks Via Offline Decision Transformer
Xu; Wu; Jenkin; Jang; Liu; Dudek] Yi Tian Xu; Di Wu; Michael Jenkin; Seowoo Jang; Xue Liu; Gregory Dudek.

2024Proc. ICC 2024 - IEEE International Conference on Communications
Abstract
Abstract
With the global aim of reducing carbon emissions, energy saving for communication systems has gained tremendous attention. Efficient energy-saving solutions are not only required to accommodate the fast growth in communication demand but solutions are also challenged by the complex nature of the load dynamics. Recent reinforcement learning (RL)-based methods have shown promising performance for network optimization problems, such as base station energy saving. However, a major limitation of these methods is the requirement
Topics
reinforcement learningtelecommunications
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@inproceedings{Xu2024, author = {Yi Tian Xu and Di Wu and Michael Jenkin and Seowoo Jang and Xue Liu and Gregory Dudek}, title = {Optimizing Energy Saving for Wireless Networks Via Offline Decision Transformer}, booktitle = {Proc. ICC 2024 - IEEE International Conference on Communications}, year = {2024}, pages = {409--414}, doi = {10.1109/ICC51166.2024.10622786}, address = {Denver, CO, USA} }
PEOPLEx: PEdestrian Opportunistic Positioning LEveraging IMU, UWB, BLE and WiFi
Lajoie; Pierre-Yves; Bobak Hamed Baghi; Sachini Herath; Francois Hogan; Xue Liu; Gregory Dudek.

2024ICC 2024-IEEE International Conference on CommunicationsICC 2024 best paper award recipient
Abstract
Abstract
This paper advances the field of pedestrian localization by introducing a unifying framework for opportunistic positioning based on nonlinear factor graph optimization. While many existing approaches assume constant availability of one or multiple sensing signals, our methodology employs IMU-based pedestrian inertial navigation as the backbone for sensor fusion, opportunistically integrating Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), and WiFi signals when they are available in the environment. The proposed PEOPLEx framework is designed to incorporate sensing data as it becomes available, operating without any prior knowledge about the environment (e.g. anchor locations, radio frequency maps, etc.). Our contributions are twofold: 1) we introduce an opportunistic multi-sensor and real-time pedestrian positioning framework fusing the available sensor measurements; 2) we develop novel factors for adaptive scaling and coarse loop closures, significantly improving the precision of indoor positioning. Experimental validation confirms that our approach achieves accurate localization estimates in real indoor scenarios using commercial smartphones.
Topics
localization
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@inproceedings{lajoie2024peoplex, author = {Pierre-Yves Lajoie and Bobak Hamed Baghi and Sachini Herath and Francois Hogan and Xue Liu and Gregory Dudek}, title = {PEOPLEx: PEdestrian Opportunistic Positioning LEveraging IMU, UWB, BLE and WiFi}, booktitle = {ICC 2024-IEEE International Conference on Communications}, pages = {3518--3523}, year = {2024}, publisher = {IEEE}, note = {ICC 2024 best paper award recipient} }
PhotoBot: Reference-Guided Interactive Photography via Natural Language
Limoyo; O.; J. Li; D. Rivkin; J. Kelly; G. Dudek

2024Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We introduce PhotoBot, a framework for automated photo acquisition based on an interplay between high-level human language guidance and a robot photographer. We propose to communicate photography suggestions to the user via a reference picture that is retrieved from a curated gallery. We exploit a visual language model (VLM) and an object detector to characterize reference pictures via textual descriptions and use a large language model (LLM) to retrieve relevant reference pictures based on a user's language query through text
Topics
generative aihuman-robot interaction
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@inproceedings{Limoyo2024, author = {O. Limoyo and J. Li and D. Rivkin and J. Kelly and G. Dudek}, title = {PhotoBot: Reference-Guided Interactive Photography via Natural Language}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2024}, url = {http://arxiv.org/abs/2401.11061}, note = {Also arXiv, Mar. 20, 2024} }
Probabilistic Mobility Load Balancing for Multi-Band 5G and Beyond Networks
Al Lahham; Saria; Di Wu; Ekram Hossain; Xue Liu; Gregory Dudek.

20242024 IEEE International Conference on Communications Workshops (ICC Workshops)
Abstract
Abstract
The ever-increasing demand for data services and the proliferation of user equipment (UE) have resulted in a significant rise in the volume of mobile traffic. Moreover, in multi-band networks, non-uniform traffic distribution among different operational bands can lead to congestion, which can adversely impact the user's quality of experience. Load balancing is a critical aspect of network optimization, where it ensures that the traffic is evenly distributed among different bands, avoiding congestion and ensuring bett er user experience
Topics
telecommunications
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@inproceedings{al2024probabilistic, title={Probabilistic Mobility Load Balancing for Multi-Band 5G and Beyond Networks}, author={Al Lahham, Saria and Wu, Di and Hossain, Ekram and Liu, Xue and Dudek, Gregory}, booktitle={2024 IEEE International Conference on Communications Workshops (ICC Workshops)}, pages={1673--1678}, year={2024}, organization={IEEE}, note={Also available: \url{http://arxiv.org/abs/2401.13792}} }
Reference-Guided Robotic Photography Through Natural Language Interaction
O. Limoyo; J. Li; D. Rivkin; J. Kelly; G. Dudek

20242024
Abstract
Abstract
Reference-Guided Robotic Photography Through Natural Language Interaction
Topics
generative aihuman-robot interactionobject recognition
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@misc{referenceguidedroboticphotographythrough, author = {O. Limoyo and J. Li and D. Rivkin and J. Kelly and G. Dudek}, title = {Reference-Guided Robotic Photography Through Natural Language Interaction}, year = {2024}, journal = {2024}, }
Uncertainty-Aware Hybrid Paradigm of Nonlinear MPC and Model-Based RL for Offroad Navigation: Exploration of Transformers in the Predictive Model
Lotfi; Faraz; Virji; Khalil ; Faraji; Farnoosh; Berry; Lucas; Holliday; Andrew; Meger; David Paul; Dudek; Gregory

2024Proc. International Conference on Robotics and Automation
Abstract
Abstract
In this paper, we investigate a hybrid scheme that combines nonlinear model predictive control (MPC) and model-based reinforcement learning (RL) for navigation planning of an autonomous model car across offroad, unstructured terrains without relying on predefined maps. Our innovative approach takes inspiration from BADGR, an LSTM-based network that primarily concentrates on environment modeling, but distinguishes itself by substituting LSTM modules with transformers to greatly elevate the performance of our model
Topics
deep learningexploration strategiesgenerative aipath planningreinforcement learning
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@inproceedings{lotfi2024uncertainty, title={Uncertainty-Aware Hybrid Paradigm of Nonlinear MPC and Model-Based RL for Offroad Navigation: Exploration of Transformers in the Predictive Model}, author={Lotfi, Faraz and Virji, Khalil and Faraji, Farnoosh and Berry, Lucas and Holliday, Andrew and Meger, David Paul and Dudek, Gregory}, booktitle={Proc. International Conference on Robotics and Automation}, year={2024}, month={May} }
Visual-Tactile Inference of 2.5 D Object Shape From Marker Texture
A Jilani; F Hogan; C Morissette; G Dudek

2024IEEE Robotics and …
Abstract
Abstract
Visual-tactile sensing affords abundant capabilities for contact-rich object manipulation tasks including grasping and placing. Here we introduce a shape-from-texture inspired contact shape estimation approach for visual-tactile sensors equipped with visually distinct membrane markers. Under a perspective projection camera model, measurements related to the change in marker separation upon contact are used to recover surface shape. Our approach allows for shape sensing in real time, without requiring network training or
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@misc{visualtactileinferenceof25dobjectshapefr, author = {A Jilani and F Hogan and C Morissette and G Dudek}, title = {Visual-Tactile Inference of 2.5 D Object Shape From Marker Texture}, year = {2024}, journal = {IEEE Robotics and …}, url = {https://ieeexplore.ieee.org/abstract/document/10803047/}, }
Working backwards: Learning to Place by Picking
Limoyo, O.; Konar, A.; Ablett, T.; Kelly, J.; Hogan, F.; Dudek, G.

2024Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We present Learning to Place by Picking (LPP), a method capable of autonomously collecting demonstrations for a family of placing tasks in which objects must be manipulated to specific locations. With LPP, we approach the learning of robotic object placement policies by reversing the grasping process and exploiting the inherent symmetry of the pick and place problems. Specifically, we obtain placing demonstrations from a set of grasp sequences of objects that are initially located at their target placement locations. Our system
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@inproceedings{limoyo2024working, title={Working backwards: Learning to Place by Picking}, author={Limoyo, O. and Konar, A. and Ablett, T. and Kelly, J. and Hogan, F. and Dudek, G.}, booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year={2024} }
A Generic Framework for ``Byzantine-tolerant Consensus Achievement in Robot Swarms''
Hanqing Zhao; Alexandre Pacheco; Volker Strobel; Andreagiovanni Reina; Xue Liu; Gregory Dudek; Marco Dorigo

2023Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)
Abstract
Abstract
Byzantine-tolerant Consensus Achievement in Robot Swarms
Topics
anomaly detectioncomplexity boundscooperative localizationrobotic collectivestelecommunications
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@inproceedings{zhao2023byzantine, author = {Hanqing Zhao and Alexandre Pacheco and Volker Strobel and Andreagiovanni Reina and Xue Liu and Gregory Dudek and Marco Dorigo}, title = {A Generic Framework for ``Byzantine-tolerant Consensus Achievement in Robot Swarms''}, booktitle = {Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)}, year = {2023}, month = {Oct.}, pages = {8} }
A Generic Framework for Byzantine-tolerant Consensus Achievement in Robot Swarms
Hanqing Zhao; Alexandre Pacheco; Volker Strobel; Andreagiovanni Reina; Xue Liu; Gregory Dudek; Marco Dorigo

2023Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)
Abstract
Abstract
Recent studies show that some security features that blockchains grant to decentralized networks on the internet can be ported to swarm robotics. Although the integration of blockchain technology and swarm robotics shows great promise, thus far, research has been limited to proof-of-concept scenarios where the blockchain-based mechanisms are tailored to a particular swarm task and operating environment. In this study, we propose a generic framework based on a blockchain smart contract that enables robot swarms to
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@inproceedings{Zhao2023Byzantine, author = {Hanqing Zhao and Alexandre Pacheco and Volker Strobel and Andreagiovanni Reina and Xue Liu and Gregory Dudek and Marco Dorigo}, title = {A Generic Framework for Byzantine-tolerant Consensus Achievement in Robot Swarms}, booktitle = {Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)}, year = {2023}, month = {October}, pages = {8 pages} }
A Study of Human-Robot Handover through Human-Human Object Transfer
C. Morissette; B. H. Baghi; F. R. Hogan; G. Dudek

2023arXiv preprint arXiv:2311.13021, 2023
Abstract
Abstract
A Study of Human-Robot Handover through Human-Human Object Transfer
Topics
human-robot interaction
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@misc{astudyofhumanrobothandoverthroughhumanhu, author = {C. Morissette and B. H. Baghi and F. R. Hogan and G. Dudek}, title = {A Study of Human-Robot Handover through Human-Human Object Transfer}, year = {2023}, journal = {arXiv preprint arXiv:2311.13021, 2023}, }

AdaTeacher: Adaptive Multi-Teacher Weighting for Communication Load Forecasting

Hu, Chengming; Wang, Ju; Wu, Di; Xin, Yan; Zhang, Charlie; Liu, Xue; Dudek, Gregory

2023GLOBECOM 2023-2023 IEEE Global Communications Conference

Abstract

To deal with notorious delays in communication systems, it is crucial to forecast key system characteristics, such as the communication load. Most existing studies aggregate data from multiple edge nodes for improving the forecasting accuracy. However, the bandwidth cost of such data aggregation could be unacceptably high from the perspective of system operators. To achieve both the high forecasting accuracy and bandwidth efficiency, this paper proposes an Adaptive Multi-Teacher Weighting in Teacher-Student Learning approach

Topics

adaptive controlcomplexity boundsknowledge distillationreinforcement learningtelecommunications

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@inproceedings{hu2023adateacher,
 abstract = {To deal with notorious delays in communication systems, it is crucial to forecast key system characteristics, such as the communication load. Most existing studies aggregate data from multiple edge nodes for improving the forecasting accuracy. However, the bandwidth cost of such data aggregation could be unacceptably high from the perspective of system operators. To achieve both the high forecasting accuracy and bandwidth efficiency, this paper proposes an Adaptive Multi-Teacher Weighting in Teacher-Student Learning approach},
 author = {Hu, Chengming and Wang, Ju and Wu, Di and Xin, Yan and Zhang, Charlie and Liu, Xue and Dudek, Gregory},
 booktitle = {GLOBECOM 2023-2023 IEEE Global Communications Conference},
 organization = {IEEE},
 pages = {7399--7404},
 pub_year = {2023},
 title = {AdaTeacher: Adaptive Multi-Teacher Weighting for Communication Load Forecasting},
 venue = {… 2023-2023 IEEE …}
}

Ansel photobot: A robot event photographer with semantic intelligence

Rivkin; D.; G. Dudek; N. Kakodkar; D. Meger; O. Limoyo; M. Jenkin; X. Liu; F. Hogan

20232023 IEEE International Conference on Robotics and Automation (ICRA)

Abstract

Our work examines the way in which large language models can be used for robotic planning and sampling in the context of automated photographic documentation. Specifically, we illustrate how to produce a photo-taking robot with an exceptional level of semantic awareness by leveraging recent advances in general purpose language (LM) and vision-language (VLM) models. Given a high-level description of an event we use an LM to generate a natural-language list of photo descriptions that one would expect a photographer

Topics

generative aihuman-robot interactionobject recognition

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@inproceedings{rivkin2023ansel,
 abstract = {Our work examines the way in which large language models can be used for robotic planning and sampling in the context of automated photographic documentation. Specifically, we illustrate how to produce a photo-taking robot with an exceptional level of semantic awareness by leveraging recent advances in general purpose language (LM) and vision-language (VLM) models. Given a high-level description of an event we use an LM to generate a natural-language list of photo descriptions that one would expect a photographer},
 author = {Rivkin, Dmitriy and Dudek, Gregory and Kakodkar, Nikhil and Meger, David and Limoyo, Oliver and Jenkin, Michael and Liu, Xue and Hogan, Francois},
 booktitle = {2023 IEEE International Conference on Robotics and Automation (ICRA)},
 organization = {IEEE},
 pages = {8262--8268},
 pub_year = {2023},
 title = {Ansel photobot: A robot event photographer with semantic intelligence},
 venue = {… on Robotics and …}
}

Augmenting Transit Network Design Algorithms with Deep Learning
A. Holliday; G. Dudek

2023in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023
Abstract
Abstract
Augmenting Transit Network Design Algorithms with Deep Learning
Topics
deep learning
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@misc{augmentingtransitnetworkdesignalgorithms, author = {A. Holliday and G. Dudek}, title = {Augmenting Transit Network Design Algorithms with Deep Learning}, year = {2023}, booktitle = {in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023}, }
Communication Load Balancing via Efficient Inverse Reinforcement Learning
Konar, Abhisek; Wu, Di; Xu, Yi Tian; Jang, Seowoo; Liu, Steve; Dudek, Gregory

2023IEEE International Conference on Communications (ICC)
Abstract
Abstract
Communication load balancing aims to balance the load between different available resources, and thus improve the quality of service for network systems. After formulating the load balancing (LB) as a Markov decision process problem, reinforcement learning (RL) has recently proven effective in addressing the LB problem. To leverage the benefits of classical RL for load balancing, however, we need an explicit reward definition. Engineering this reward function is challenging, because it involves the need for expert knowledge and there
Topics
inverse reinforcement learningreinforcement learningtelecommunications
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@inproceedings{konar2023communication, title={Communication Load Balancing via Efficient Inverse Reinforcement Learning}, author={Konar, Abhisek and Wu, Di and Xu, Yi Tian and Jang, Seowoo and Liu, Steve and Dudek, Gregory}, booktitle={IEEE International Conference on Communications (ICC)}, year={2023}, location={Rome, Italy} }

CPMR 3rd Edition: Software Infrastructure

G. Dudek; M. Jenkin

20232023

Abstract

CPMR 3rd Edition: Software Infrastructure

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@misc{cpmr3rdeditionsoftwareinfrastructure2023,
  author = {G. Dudek and M. Jenkin},
  title = {CPMR 3rd Edition: Software Infrastructure},
  year = {2023},
  journal = {2023},
}

Eliminating space scanning: Fast mmWave beam alignment with UWB radios
Wang; J.; X. Chen; X. Liu; G. Dudek

2023ACM Transactions on Sensor …
Abstract
Abstract
Due to their large bandwidth and impressive data speed, millimeter-wave (mmWave) radios are expected to play a key role in the 5G and beyond (eg, 6G) communication networks. Yet, to release mmWave's true power, the highly directional mmWave beams need to be aligned perfectly. Most existing beam alignment methods adopt an exhaustive or semi-exhaustive space scanning, which introduces up to seconds of delays. To eliminate the need for complex space scanning, this article presents an Ultra-wideband (UWB)-assisted mmWave
Topics
telecommunications
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@misc{eliminatingspacescanningfastmmwavebeamal, author = {Wang and J. and X. Chen and X. Liu and G. Dudek}, title = {Eliminating space scanning: Fast mmWave beam alignment with UWB radios}, year = {2023}, journal = {ACM Transactions on Sensor …}, url = {https://dl.acm.org/doi/abs/10.1145/3588438}, }

Energy Saving in Cellular Wireless Networks via Transfer Deep Reinforcement Learning

Wu, Di; Xu, Yi Tian; Jenkin, Michael; Jang, Seowoo; Hossain, Ekram; Liu, Xue; Dudek, Gregory

2023GLOBECOM 2023-2023 IEEE Global Communications Conference

Abstract

With the increasing use of data-intensive mobile applications and the number of mobile users, the demand for wireless data services has been increasing exponentially in recent years. In order to address this demand, a large number of new cellular base stations are being deployed around the world, leading to a significant increase in energy consumption and greenhouse gas emission. Consequently, energy consumption has emerged as a key concern in the fifth-generation (5G) network era and beyond. Reinforcement learning (RL)

Topics

knowledge distillationtelecommunications

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@inproceedings{wu2023energy,
 abstract = {With the increasing use of data-intensive mobile applications and the number of mobile users, the demand for wireless data services has been increasing exponentially in recent years. In order to address this demand, a large number of new cellular base stations are being deployed around the world, leading to a significant increase in energy consumption and greenhouse gas emission. Consequently, energy consumption has emerged as a key concern in the fifth-generation (5G) network era and beyond. Reinforcement learning (RL)},
 author = {Wu, Di and Xu, Yi Tian and Jenkin, Michael and Jang, Seowoo and Hossain, Ekram and Liu, Xue and Dudek, Gregory},
 booktitle = {GLOBECOM 2023-2023 IEEE Global Communications Conference},
 organization = {IEEE},
 pages = {7019--7024},
 pub_year = {2023},
 title = {Energy Saving in Cellular Wireless Networks via Transfer Deep Reinforcement Learning},
 venue = {… 2023-2023 IEEE …}
}

Hypernetworks for zero-shot transfer in reinforcement learning

Rezaei-Shoshtari; S.; C. Morissette; F.R. Hogan; G. Dudek; D. Meger

2023Proceedings of the AAAI Conference on Artificial Intelligence

Abstract

In this paper, hypernetworks are trained to generate behaviors across a range of unseen task conditions, via a novel TD-based training objective and data from a set of near-optimal RL solutions for training tasks. This work relates to meta RL, contextual RL, and transfer learning, with a particular focus on zero-shot performance at test time, enabled by knowledge of the task parameters (also known as context). Our technical approach is based upon viewing each RL algorithm as a mapping from the MDP specifics to the near-optimal

Topics

knowledge distillationreinforcement learning

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@inproceedings{rezaei2023hypernetworks,
 abstract = {In this paper, hypernetworks are trained to generate behaviors across a range of unseen task conditions, via a novel TD-based training objective and data from a set of near-optimal RL solutions for training tasks. This work relates to meta RL, contextual RL, and transfer learning, with a particular focus on zero-shot performance at test time, enabled by knowledge of the task parameters (also known as context). Our technical approach is based upon viewing each RL algorithm as a mapping from the MDP specifics to the near-optimal},
 author = {Rezaei-Shoshtari, Sahand and Morissette, Charlotte and Hogan, Francois R and Dudek, Gregory and Meger, David},
 booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
 number = {8},
 pages = {9579--9587},
 pub_year = {2023},
 title = {Hypernetworks for zero-shot transfer in reinforcement learning},
 venue = {Proceedings of the …},
 volume = {37}
}

Learning to Adapt: Communication Load Balancing via Adaptive Deep Reinforcement Learning

Wu, Di; Xu, Yi Tian; Li, Jimmy; Jenkin, Michael; Hossain, Ekram; Jang, Seowoo; Xin, Yan; Zhang, Charlie; Liu, Xue; Dudek, Gregory

2023GLOBECOM 2023-2023 IEEE Global Communications Conference

Abstract

The association of mobile devices with network resources (eg, base stations, frequency bands/channels), known as load balancing, is critical to reduce communication traffic congestion and network performance. Reinforcement learning (RL) has shown to be effective for communication load balancing and achieves better performance than currently used rule-based methods, especially when the traffic load changes quickly. However, RL-based methods usually need to interact with the environment for a large number of time

Topics

knowledge distillationreinforcement learningtelecommunications

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@inproceedings{wu2023learning,
 abstract = {The association of mobile devices with network resources (eg, base stations, frequency bands/channels), known as load balancing, is critical to reduce communication traffic congestion and network performance. Reinforcement learning (RL) has shown to be effective for communication load balancing and achieves better performance than currently used rule-based methods, especially when the traffic load changes quickly. However, RL-based methods usually need to interact with the environment for a large number of time},
 author = {Wu, Di and Xu, Yi Tian and Li, Jimmy and Jenkin, Michael and Hossain, Ekram and Jang, Seowoo and Xin, Yan and Zhang, Charlie and Liu, Xue and Dudek, Gregory},
 booktitle = {GLOBECOM 2023-2023 IEEE Global Communications Conference},
 organization = {IEEE},
 pages = {2973--2978},
 pub_year = {2023},
 title = {Learning to Adapt: Communication Load Balancing via Adaptive Deep Reinforcement Learning},
 venue = {… 2023-2023 IEEE …}
}

Mixed-Variable PSO with Fairness on Multi-Objective Field Data Replication in Wireless Networks
Dun Yuan; Yujin Nam; Amal Feriani; Abhisek Konar; Di Wu; Seowoo Jang; Xue Liu; Greg Dudek

2023Proc. IEEE International Conference on Communications (ICC)
Abstract
Abstract
Digital twins have shown a great potential in supporting the development of wireless networks. They are virtual representations of 5G/6G systems enabling the design of machine learning and optimization-based techniques. Field data replication is one of the critical aspects of building a simulation-based twin, where the objective is to calibrate the simulation to match field performance measurements. Since wireless networks involve a variety of key performance indicators (KPIs), the replication process becomes a multi-objective
Topics
telecommunications
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@inproceedings{yuan2023mixed, author = {Dun Yuan and Yujin Nam and Amal Feriani and Abhisek Konar and Di Wu and Seowoo Jang and Xue Liu and Greg Dudek}, title = {Mixed-Variable PSO with Fairness on Multi-Objective Field Data Replication in Wireless Networks}, booktitle = {Proc. IEEE International Conference on Communications (ICC)}, year = {2023} }
Multi-agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks
Kang; Jikun; Wu; Di; Wang; Ju; Hossain; Ekram; Liu; Xue; Dudek; Gregory

2023IEEE International Conference on Communications (ICC)
Abstract
Abstract
In cellular networks, User Equipment (UE) handoff from one Base Station (BS) to another, giving rise to the load balancing problem among the BSs. To address this problem, BSs can work collaboratively to deliver a smooth migration (or handoff) and satisfy the UEs' service requirements. This paper formulates the load balancing problem as a Markov game and proposes a Robust Multi-agent Attention Actor-Critic (Robust-MA3C) algorithm that can facilitate collaboration among the BSs (ie, agents). In particular, to solve the Markov game
Topics
reinforcement learningtelecommunications
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@inproceedings{kang2023multi, title={Multi-agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks}, author={Kang, Jikun and Wu, Di and Wang, Ju and Hossain, Ekram and Liu, Xue and Dudek, Gregory}, booktitle={IEEE International Conference on Communications (ICC)}, year={2023}, address={Rome, Italy}, doi={10.48550/arXiv.2303.08003} }
Neural bee colony optimization: A case study in public transit network design
A Holliday; G Dudek

2023arXiv preprint arXiv:2306.00720
Abstract
Abstract
In this work we explore the combination of metaheuristics and learned neural network solvers for combinatorial optimization. We do this in the context of the transit network design problem, a uniquely challenging combinatorial optimization problem with real-world importance. We train a neural network policy to perform single-shot planning of individual transit routes, and then incorporate it as one of several sub-heuristics in a modified Bee Colony Optimization (BCO) metaheuristic algorithm. Our experimental results demonstrate
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@misc{neuralbeecolonyoptimizationacasestudyinp, author = {A Holliday and G Dudek}, title = {Neural bee colony optimization: A case study in public transit network design}, year = {2023}, journal = {arXiv preprint arXiv:2306.00720}, url = {https://arxiv.org/abs/2306.00720}, }
Push it to the Demonstrated Limit: Multimodal Visuotactile Imitation Learning with Force Matching
Ablett; Trevor; Oliver Limoyo; Adam Sigal; Affan Jilani; Jonathan Kelly; Kaleem Siddiqi; Francois Hogan; Gregory Dudek.

2023arXiv preprint arXiv:2311.01248
Abstract
Abstract
Optical tactile sensors have emerged as an effective means to acquire dense contact information during robotic manipulation. A recently-introducedsee-through-your-skin'(STS) variant of this type of sensor has both visual and tactile modes, enabled by leveraging a semi-transparent surface and controllable lighting. In this work, we investigate the benefits of pairing visuotactile sensing with imitation learning for contact-rich manipulation tasks. First, we use tactile force measurements and a novel algorithm during kinesthetic teaching to yield
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@article{ablett2023push, title={Push it to the Demonstrated Limit: Multimodal Visuotactile Imitation Learning with Force Matching}, author={Ablett, Trevor and Limoyo, Oliver and Sigal, Adam and Jilani, Affan and Kelly, Jonathan and Siddiqi, Kaleem and Hogan, Francois and Dudek, Gregory}, journal={arXiv preprint arXiv:2311.01248}, year={2023} }
Realizing XR applications using 5G-based 3D holographic communication and mobile edge computing
D Yuan; E Hossain; D Wu; X Liu; G Dudek

2023arXiv preprint arXiv …
Abstract
Abstract
3D holographic communication has the potential to revolutionize the way people interact with each other in virtual spaces, offering immersive and realistic experiences. However, demands for high data rates, extremely low latency, and high computations to enable this technology pose a significant challenge. To address this challenge, we propose a novel job scheduling algorithm that leverages Mobile Edge Computing (MEC) servers in order to minimize the total latency in 3D holographic communication. One of the motivations for this
Topics
telecommunications
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@misc{realizingxrapplicationsusing5gbased3dhol, author = {D Yuan and E Hossain and D Wu and X Liu and G Dudek}, title = {Realizing XR applications using 5G-based 3D holographic communication and mobile edge computing}, year = {2023}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2310.03908}, }
Reinforcement learning for communication load balancing: approaches and challenges
Wu; D.; J. Li; A. Feriani; Y.T. Xu; M. Jenkin; S. Jang; X. Liu; G. Dudek

2023Frontiers in Computer …
Abstract
Abstract
The amount of cellular communication network traffic has increased dramatically in recent years, and this increase has led to a demand for enhanced network performance. Communication load balancing aims to balance the load across available network resources and thus improve the quality of service for network users. Most existing load balancing algorithms are manually designed and tuned rule-based methods where near-optimality is almost impossible to achieve. Furthermore, rule-based methods are difficult to
Topics
adaptive controlknowledge distillationreinforcement learningtelecommunications
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@misc{reinforcementlearningforcommunicationloa, author = {Wu and D. and J. Li and A. Feriani and Y.T. Xu and M. Jenkin and S. Jang and X. Liu and G. Dudek}, title = {Reinforcement learning for communication load balancing: approaches and challenges}, year = {2023}, journal = {Frontiers in Computer …}, url = {https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2023.1156064/full}, }

Robust Scuba Diver Tracking and Recovery in Open Water Using YOLOv7, SORT, and Spiral Search

Lotfi, Faraz; Virji, Khalil; Dudek, Gregory

20232023 20th Conference on Robots and Vision (CRV)

Abstract

Target tracking is a classic problem in computer vision, with numerous applications in robotics. However, tracking targets underwater presents additional complications due to the six degrees of freedom nature of the problem and the challenging visual environment. In this paper, we address the problem of robotic underwater tracking of scuba divers by partitioning it into two parts: vision and control. We propose a new approach that exploits a highly-maneuverable underwater robot to perform experiments in open water, coupling sensing

Topics

exploration strategieslocalizationobject recognitionrobotic collectivesunderwater navigationunderwater robotics

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@inproceedings{lotfi2023robust,
 abstract = {Target tracking is a classic problem in computer vision, with numerous applications in robotics. However, tracking targets underwater presents additional complications due to the six degrees of freedom nature of the problem and the challenging visual environment. In this paper, we address the problem of robotic underwater tracking of scuba divers by partitioning it into two parts: vision and control. We propose a new approach that exploits a highly-maneuverable underwater robot to perform experiments in open water, coupling sensing},
 author = {Lotfi, Faraz and Virji, Khalil and Dudek, Gregory},
 booktitle = {2023 20th Conference on Robots and Vision (CRV)},
 organization = {IEEE},
 pages = {233--240},
 pub_year = {2023},
 title = {Robust Scuba Diver Tracking and Recovery in Open Water Using YOLOv7, SORT, and Spiral Search},
 venue = {2023 20th Conference on Robots and …}
}

Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks
Kozlov, Igor; Rivkin, Dmitriy; Chang, Wei-Di; Wu, Di; Liu, Xue; Dudek, Gregory

2023Proc. IEEE International Conference on Communications (ICC)
Abstract
Abstract
Radio Access Networks (RANs) for telecommunications represent large agglomerations of interconnected hardware consisting of hundreds of thousands of transmitting devices (cells). Such networks undergo frequent and often heterogeneous changes caused by network operators, who are seeking to tune their system parameters for optimal performance. The effects of such changes are challenging to predict and will become even more so with the adoption of fifth-generation/sixth-generation (5G/6G) networks. Therefore, RAN monitoring is
Topics
anomaly detectionknowledge distillationtelecommunications
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@inproceedings{kozlov2023self, title={Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks}, author={Kozlov, Igor and Rivkin, Dmitriy and Chang, Wei-Di and Wu, Di and Liu, Xue and Dudek, Gregory}, booktitle={Proc. IEEE International Conference on Communications (ICC)}, year={2023}, doi={10.48550/arXiv.2302.02025} }
Zero-shot Fault Detection for Manipulators through Bayesian Inverse Reinforcement Learning
Hanqing Zhao; Xue Liu; Gregory Dudek

2023Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)
Abstract
Abstract
We consider the detection of faults in robotic manipulators, with particular emphasis on faults that have not been observed or identified in advance, which naturally includes those that occur very infrequently. Recent studies indicate that the reward function obtained through Inverse Reinforcement Learning (IRL) can help detect anomalies caused by faults in a control system (ie fault detection). Current IRL methods for fault detection, however, either use a linear reward representation or require extensive sampling from the environment to
Topics
anomaly detectionbayesian inferenceinverse reinforcement learning
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@inproceedings{zhao2023zero, author = {Hanqing Zhao and Xue Liu and Gregory Dudek}, title = {Zero-shot Fault Detection for Manipulators through Bayesian Inverse Reinforcement Learning}, booktitle = {Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)}, year = {2023}, month = {Oct.}, pages = {8} }
A Generalized Load Balancing Policy With Multi-Teacher Reinforcement Learning
Kang; Jikun; Ju Wang; Chengming Hu; Xue Liu; Gregory Dudek (2022).

2022Proceedings of GLOBECOM 2022-2022 IEEE Global Communications Conference
Abstract
Abstract
Although reinforcement learning (RL) shows advantages in cellular network load balancing, it suffers from a low generalization ability, preventing it from real-world applications. Specifically, if network traffic pattern changes, the learned RL policy cannot adapt accordingly, resulting in system performance degradation. To address this issue, we propose a Multi-teacher MOdel BAsed Reinforcement Learning algorithm (MOBA), which leverages multi-teacher knowledge distillation theory to learn a generalized load balancing
Topics
adaptive controlcomplexity boundsknowledge distillationreinforcement learningtelecommunications
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@inproceedings{Kang2022, author = {Jikun Kang and Ju Wang and Chengming Hu and Xue Liu and Gregory Dudek}, title = {A Generalized Load Balancing Policy With Multi-Teacher Reinforcement Learning}, booktitle = {Proceedings of GLOBECOM 2022-2022 IEEE Global Communications Conference}, year = {2022}, pages = {3096--3101}, publisher = {IEEE} }
Accurate Communication Traffic Forecasting with Multi-Source Adaptive Feature Boosting
Hu; Chengming; Ju Wang; Di Wu; Xue Liu; Gregory Dudek (2022).

2022Proc. GLOBECOM 2022-2022 IEEE Global Communications Conference
Abstract
Abstract
Advanced communication network functions, such as resource allocation and dynamic spectrum management, heavily rely on the accurate forecasting of traffic. Data-driven solutions, eg, Neural Network (NN) based forecasting methods, have been proven to be effective only when sufficient data is available. However, Base Stations (BSs) have limited data in the real world, since big data for communication networks could be extremely expensive to collect, store, and migrate. Therefore, most existing traffic forecasting methods
Topics
knowledge distillationtelecommunications
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@inproceedings{hu2022accurate, title={Accurate Communication Traffic Forecasting with Multi-Source Adaptive Feature Boosting}, author={Hu, Chengming and Wang, Ju and Wu, Di and Liu, Xue and Dudek, Gregory}, booktitle={Proc. GLOBECOM 2022-2022 IEEE Global Communications Conference}, pages={2316--2321}, year={2022}, organization={IEEE} }
Active deep multi-task learning for forecasting short-term loads
Wu; D.; M. Jenkin; X. Liu; G. Dudek

2022IEEE International Conference on Communications, ICC 2022
Abstract
Abstract
With the increasing adoption of renewable energy generation and electric devices, electric load forecasting, especially short-term load forecasting (STLF), is becoming more and more important. The widespread adoption of smart meters makes it possible to utilize complex machine learning models for both aggregated load and single-home residential load forecasting. Similar homes in nearby locations are likely to have similar load consumption patterns and this similarity can be used to improve the overall forecasting performance
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@inproceedings{wu2022active, author = {Wu, D. and Jenkin, M. and Liu, X. and Dudek, G.}, title = {Active deep multi-task learning for forecasting short-term loads}, booktitle = {IEEE International Conference on Communications, ICC 2022}, year = {2022}, pages = {5523--5529}, doi = {10.1109/ICC45855.2022.9838341} }
Attentive Knowledge Transfer for Short-term Load Forecasting
Wu; Di; Michael Jenkin; Yi Tian Xu; Xue Liu; Gregory Dudek (2022).

2022Proc GLOBECOM 2022-2022 IEEE Global Communications Conference
Abstract
Abstract
The modern power system is transitioning towards increasing penetration of renewable energy generation and demand from different types of electrical appliances. With this transition, residential load forecasting, especially short-term load forecasting (STLF), is becoming more and more challenging and important. Accurate short-term load forecasting can help improve energy dispatching efficiency and, as a consequence, reduce overall power system operation cost. Most current load forecasting algorithms assume that there is a
Topics
knowledge distillation
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@inproceedings{wu2022attentive, title={Attentive Knowledge Transfer for Short-term Load Forecasting}, author={Wu, Di and Jenkin, Michael and Xu, Yi Tian and Liu, Xue and Dudek, Gregory}, booktitle={Proc GLOBECOM 2022-2022 IEEE Global Communications Conference}, pages={5285--5291}, year={2022}, organization={IEEE} }
Bayesian Q-learning with imperfect expert demonstrations
F Che; X Zhu; D Precup; D Meger; G Dudek

2022arXiv preprint arXiv …
Abstract
Abstract
Guided exploration with expert demonstrations improves data efficiency for reinforcement learning, but current algorithms often overuse expert information. We propose a novel algorithm to speed up Q-learning with the help of a limited amount of imperfect expert demonstrations. The algorithm avoids excessive reliance on expert data by relaxing the optimal expert assumption and gradually reducing the usage of uninformative expert data. Experimentally, we evaluate our approach on a sparse-reward chain environment and six
Topics
bayesian inferencereinforcement learning
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@misc{bayesianqlearningwithimperfectexpertdemo, author = {F Che and X Zhu and D Precup and D Meger and G Dudek}, title = {Bayesian Q-learning with imperfect expert demonstrations}, year = {2022}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2210.01800}, }
Behaviour Learning with Adaptive Motif Discovery and Interacting Multiple Model
Zhao; Hanging; Travis Manderson; Hao Zhang; Xue Liu; Gregory Dudek (2022).

20222022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We propose an approach that enables simultaneous interpretable learning of a high-level discrete behaviour and its low-level rhythmic sub-behaviour. We do this though a unified reward function, where a reward function that only describes low-level behaviour, with less impact on learning of other behaviours is recovered from few-shot motion demonstrations. To this end, we first extract local behaviour motifs from state-only human demonstrations and random driving samples using an adaptive motif discovery approach derived from the Matrix
Topics
behavior cloning
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@inproceedings{zhao2022behaviour, title={Behaviour Learning with Adaptive Motif Discovery and Interacting Multiple Model}, author={Zhao, Hanging and Manderson, Travis and Zhang, Hao and Liu, Xue and Dudek, Gregory}, booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={10788--10794}, year={2022}, organization={IEEE} }
Communication Traffic Prediction with Continual Knowledge Distillation
Li; Hand; Ju Wang; C. Hu; X. Chen; X. Liu; S. Jang; G. Dudek

2022ICC 2022-IEEE International Conference on Communications
Abstract
Abstract
Accurate traffic volume estimation and prediction are essential for advanced communication network functions, such as automatic operations and predictive resource allocation. Although machine learning (ML)-based approaches achieve great success in accomplishing this goal, existing approaches suffer from two drawbacks that limit their real-world applications. First, the ML-based prediction models developed in the past might be obsolete now, since the communication traffic patterns and volumes keep changing in the real world
Topics
knowledge distillationtelecommunications
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@inproceedings{li2022communication, title={Communication Traffic Prediction with Continual Knowledge Distillation}, author={Li, Hang and Wang, Ju and Hu, Chengming and Chen, Xi and Liu, Xue and Jang, Seowoo and Dudek, Gregory}, booktitle={ICC 2022-IEEE International Conference on Communications}, pages={5481--5486}, year={2022}, publisher={IEEE} }
Coordinated Load Balancing in Mobile Edge Computing Network: a Multi-Agent DRL Approach
Ma; M.; D. Wu; Y.T. Xu; J. Li; S. Jang; X. Liu; G. Dudek

2022ICC 2022-IEEE International Conference on Communications
Abstract
Abstract
Mobile edge computing (MEC) networks have been recently adopted to accommodate the fast-growing number of mobile devices performing complicated tasks with limited hardware capability. Recently, edge nodes with communication, computation, and caching capacities are starting to be deployed in MEC networks. Due to the physical separation of these resources, efficient coordination and scheduling are important for efficient resource utilization and optimal network performance. In this paper, we study mobility load balancing
Topics
knowledge distillationreinforcement learningtelecommunications
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@inproceedings{ma2022coordinated, author = {Manyou Ma and Di Wu and Yi Tian Xu and Jimmy Li and Seowoo Jang and Xue Liu and Gregory Dudek}, title = {Coordinated Load Balancing in Mobile Edge Computing Network: a Multi-Agent DRL Approach}, booktitle = {ICC 2022-IEEE International Conference on Communications}, year = {2022}, pages = {619--624}, publisher = {IEEE} }
Data-Efficient Communication Traffic Prediction With Deep Transfer Learning
Li; H.; J. Wang; X. Chen; X. Liu; G. Dudek

2022Proc ICC 2022-IEEE International Conference on Communications
Abstract
Abstract
Prediction of future traffic load is a crucial task to support the automatic Operations, Administration, and Management (OAM) of communication networks. Existing Machine Learning (ML) models require big data to accomplish this task. However, large data sets are not always available, due to the limited storage capacity and the high storage cost at Base Stations (BSs). To solve the problem, we leverage the spatial-temporal correlation among different BSs, which allows other BSs' data to be used for the prediction of the target BS. One
Topics
knowledge distillationtelecommunications
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@inproceedings{li2022data, title={Data-Efficient Communication Traffic Prediction With Deep Transfer Learning}, author={Li, Hang and Wang, Ju and Chen, Xi and Liu, Xue and Dudek, Gregory}, booktitle={Proc ICC 2022-IEEE International Conference on Communications}, pages={3190--3195}, year={2022}, organization={IEEE} }
Efficient Neural Data Compression for Machine Type Communications via Knowledge Distillation
Hussien; Mostafa; Yi Tian Xu; Di Wu; Xue Liu; Gregory Dudek (2022).

2022GLOBECOM 2022-2022 IEEE Global Communications Conference
Abstract
Abstract
The anticipated huge number of devices and large traffic volumes impose new challenges on the communication system requirements and design. One of the main requirements of massive machine-type communication (mMTC) is to support network energy efficiency. Data compression is a widely adopted technique that enables higher energy efficiency, lower latency, and better bandwidth utilization. Unfortunately, the current compression techniques are mainly designed for human-type communications (HTC). Therefore, they consider the
Topics
knowledge distillationtelecommunications
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@inproceedings{hussien2022efficient, title={Efficient Neural Data Compression for Machine Type Communications via Knowledge Distillation}, author={Hussien, Mostafa and Xu, Yi Tian and Wu, Di and Liu, Xue and Dudek, Gregory}, booktitle={GLOBECOM 2022-2022 IEEE Global Communications Conference}, pages={1169--1174}, year={2022}, publisher={IEEE} }
Fidora: Robust WiFi-based indoor localization via unsupervised domain adaptation
Chen; X.; H. Li; C. Zhou; X. Liu; D. Wu; G. Dudek

2022IEEE Internet of Things …
Abstract
Abstract
Emerging Internet of Things (IoT) applications, such as cashier-less shopping, mobile ads targeting, and geo-based augmented reality (AR), are expected to bring us much more convenience and infotainment. To realize this amazing future, we need to feed these applications with user locations of (sub) meter-level resolution anytime and anywhere. Unfortunately, many widely used location sources are either unavailable indoor (eg, global positioning system) or coarse grained (eg, user check-ins). In order to provide ubiquitous
Topics
domain adaptationlocalization
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@misc{fidorarobustwifibasedindoorlocalizationv, author = {Chen and X. and H. Li and C. Zhou and X. Liu and D. Wu and G. Dudek}, title = {Fidora: Robust WiFi-based indoor localization via unsupervised domain adaptation}, year = {2022}, journal = {IEEE Internet of Things …}, url = {https://ieeexplore.ieee.org/abstract/document/9745151/}, }
Finger-STS: Combined proximity and tactile sensing for robotic manipulation
Hogan; F.R.; J.-F. Tremblay; B.H. Baghi; M. Jenkin; K. Siddiqi; G. Dudek

2022IEEE Robotics and …
Abstract
Abstract
This paper introduces and develops novel touch sensing technologies that enable robots to better sense and react to to intermittent contact interactions. We present Finger-STS, a robotic finger embodiment of the See-Through-your-Skin (STS) sensor that can capture 1) an “in the hand” visual perspective of an object that is being manipulated and 2) a high resolution tactile imprint of the contact geometry. We demonstrate the value of the sensor on a Bead Maze task. Here the multimodal feedback provided by the Finger-STS is leveraged
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@misc{fingerstscombinedproximityandtactilesens, author = {Hogan and F.R. and J.-F. Tremblay and B.H. Baghi and M. Jenkin and K. Siddiqi and G. Dudek}, title = {Finger-STS: Combined proximity and tactile sensing for robotic manipulation}, year = {2022}, journal = {IEEE Robotics and …}, url = {https://ieeexplore.ieee.org/abstract/document/9832483/}, }
Il-flow: Imitation learning from observation using normalizing flows
Chang; Wei-Di; Juan Camilo Gamboa Higuera; Scott Fujimoto; David Meger; Gregory Dudek (2022). ``Il-flow: Imitation learning from observation us- ing normalizing flows''. 4th Robot Learning Workshop: Self-Supervised; Lifelong Learning; NeurIPS 2021

2022arXiv preprint arXiv:2205.09251
Abstract
Abstract
We present an algorithm for Inverse Reinforcement Learning (IRL) from expert state observations only. Our approach decouples reward modelling from policy learning, unlike state-of-the-art adversarial methods which require updating the reward model during policy search and are known to be unstable and difficult to optimize. Our method, IL-flOw, recovers the expert policy by modelling state-state transitions, by generating rewards using deep density estimators trained on the demonstration trajectories, avoiding the instability issues of
Topics
inverse reinforcement learningreinforcement learningteleoperation
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@article{chang2022ilflow, title={Il-flow: Imitation learning from observation using normalizing flows}, author={Chang, Wei-Di and Gamboa Higuera, Juan Camilo and Fujimoto, Scott and Meger, David and Dudek, Gregory}, journal={arXiv preprint arXiv:2205.09251}, year={2022}, note={4th Robot Learning Workshop: Self-Supervised and Lifelong Learning, NeurIPS 2021} }
Il-flow: Imitation learning from observation using normalizing flows
Chang; Wei-Di; Juan Camilo Gamboa Higuera; Scott Fujimoto; David Meger; Gregory Dudek; Il-flow: Imitation learning from observation us- ing normalizing flows; 4th Robot Learning Workshop: Self-Supervised; Lifelong Learning; NeurIPS 2021

2022arXiv preprint arXiv:2205.09251
Abstract
Abstract
We present an algorithm for Inverse Reinforcement Learning (IRL) from expert state observations only. Our approach decouples reward modelling from policy learning, unlike state-of-the-art adversarial methods which require updating the reward model during policy search and are known to be unstable and difficult to optimize. Our method, IL-flOw, recovers the expert policy by modelling state-state transitions, by generating rewards using deep density estimators trained on the demonstration trajectories, avoiding the instability issues of
Topics
inverse reinforcement learningreinforcement learningteleoperation
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@article{chang2022ilflow, title={Il-flow: Imitation learning from observation using normalizing flows}, author={Chang, Wei-Di and Gamboa Higuera, Juan Camilo and Fujimoto, Scott and Meger, David and Dudek, Gregory}, journal={arXiv preprint arXiv:2205.09251}, year={2022}, note={4th Robot Learning Workshop: Self-Supervised and Lifelong Learning, NeurIPS 2021} }
Learning to Manipulate from Pixels on Rigid Body Robots with a Kinematic Critic
J. Hansen; K. Kastner; Y. Huang; A. Courville; D. Meger; G. Dudek

2022NA
Abstract
Abstract
This paper introduces a pixel-based actor-critic architecture featuring a differentiable Denavit-Hartenburg (DH) forward kinematics function in the critic sub-network, which achieves substantial improvement in average cumulative reward across several complex manipulation tasks and two robot arms in Robosuite [1], compared to strong baselines. Forward kinematics as described by DH parameterization for rigid-body robots is fully differentiable with respect to input joint angles, given fixed link-relative geometric
Topics
deep learningreinforcement learning
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@misc{learningtomanipulatefrompixelsonrigidbod, author = {J. Hansen and K. Kastner and Y. Huang and A. Courville and D. Meger and G. Dudek}, title = {Learning to Manipulate from Pixels on Rigid Body Robots with a Kinematic Critic}, year = {2022}, journal = {NA}, url = {https://johannah.github.io/papers/DH_paper_march_8_2022.pdf}, }
Multiobjective load balancing for multiband downlink cellular networks: A meta-reinforcement learning approach
Feriani; A.; D. Wu; Y.T. Xu; J. Li; S. Jang; E. Hossain; X. Liu; G. Dudek

2022IEEE Journal on …
Abstract
Abstract
Load balancing has become a key technique to handle the increasing traffic demand and improve the user experience. It evenly distributes the traffic across network resources by offloading users from overloaded base stations or channels to less crowded ones. Load balancing is a multi-objective optimization problem involving the automatic adjustment of several parameters to simultaneously maximize multiple network performance indicators. However, the existing methods mostly rely on single-objective approaches which lead to sub
Topics
knowledge distillationreinforcement learningtelecommunications
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@misc{multiobjectiveloadbalancingformultibandd, author = {Feriani and A. and D. Wu and Y.T. Xu and J. Li and S. Jang and E. Hossain and X. Liu and G. Dudek}, title = {Multiobjective load balancing for multiband downlink cellular networks: A meta-reinforcement learning approach}, year = {2022}, journal = {IEEE Journal on …}, url = {https://ieeexplore.ieee.org/abstract/document/9855432/}, }
Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios
Tian Xu; Y.; J. Li; D. Wu; M. Jenkin; S. Jang; X. Liu; G. Dudek

2022Proc. IEEE International Conference on Communications (ICC)
Abstract
Abstract
With the continuous growth in communication network complexity and traffic volume, communication load balancing solutions are receiving increasing attention. Specifically, reinforcement learning (RL)-based methods have shown impressive performance compared with traditional rule-based methods. However, standard RL methods generally require an enormous amount of data to train, and generalize poorly to scenarios that are not encountered during training. We propose a policy reuse framework in which a policy
Topics
adaptive controlreinforcement learningtelecommunications
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@inproceedings{xu2022policy, author = {Tian Xu and J. Li and D. Wu and M. Jenkin and S. Jang and X. Liu and G. Dudek}, title = {Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios}, booktitle = {Proc. IEEE International Conference on Communications (ICC)}, year = {2022}, pages = {619--624}, address = {Rome, Italy} }
Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios
Tian Xu; Y.; J. Li; D. Wu; M. Jenkin; S. Jang; X. Liu; G. Dudek

2022Proc. IEEE International Conference on Communications (ICC)
Abstract
Abstract
With the continuous growth in communication network complexity and traffic volume, communication load balancing solutions are receiving increasing attention. Specifically, reinforcement learning (RL)-based methods have shown impressive performance compared with traditional rule-based methods. However, standard RL methods generally require an enormous amount of data to train, and generalize poorly to scenarios that are not encountered during training. We propose a policy reuse framework in which a policy
Topics
adaptive controlreinforcement learningtelecommunications
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@inproceedings{xu2022policy, author = {Tian Xu and J. Li and D. Wu and M. Jenkin and S. Jang and X. Liu and G. Dudek}, title = {Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios}, booktitle = {Proc. IEEE International Conference on Communications (ICC)}, year = {2022}, pages = {619--624}, address = {Rome, Italy} }
Scalable multirobot planning for informed spatial sampling
Manjanna; S.; A. Hsieh; G. Dudek

2022Autonomous Robots
Abstract
Abstract
This paper presents a distributed scalable multi-robot planning algorithm for informed sampling of quasistatic spatials fields. We address the problem of efficient data collection using multiple autonomous vehicles and consider the effects of communication between multiple robots, acting independently, on the overall sampling performance of the team. We focus on the distributed sampling problem where the robots operate independent of their teammates, but have the ability to communicate their current state to other neighbors within
Topics
adaptive samplinglocalizationpath planningreinforcement learningslamunderwater robotics
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@misc{scalablemultirobotplanningforinformedspa, author = {Manjanna and S. and A. Hsieh and G. Dudek}, title = {Scalable multirobot planning for informed spatial sampling}, year = {2022}, journal = {Autonomous Robots}, url = {https://link.springer.com/article/10.1007/s10514-022-10048-7}, }
SESNO: Sample Efficient Social Navigation from Observation
Baghi; Bobak H; Abhisek Konar; Francois Hogan; Michael Jenkin; Gregory Dudek (2022).

20222022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
In this paper, we present the Sample Efficient Social Navigation from Observation (SESNO) algorithm that efficiently learns socially-compliant navigation policies from observations of human trajectories. SESNO is an inverse reinforcement learning (IRL)-based algorithm that learns from human trajectory observations without knowledge of their actions. We improve the sample-efficiency over previous IRL-based methods by introducing a shared experience replay buffer that allows reuse of past trajectory experiences to estimate the policy and the
Topics
human-robot interactioninverse reinforcement learning
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@inproceedings{Baghi2022, author = {Baghi, Bobak H and Konar, Abhisek and Hogan, Francois and Jenkin, Michael and Dudek, Gregory}, title = {SESNO: Sample Efficient Social Navigation from Observation}, booktitle = {2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2022}, pages = {9164--9171}, publisher = {IEEE} }
Short-term load forecasting with deep boosting transfer regression
Wu; D.; Y.T. Xu; M. Jenkin; J. Wang; H. Li; X. Liu; G. Dudek

2022ICC 2022-IEEE International Conference on Communications
Abstract
Abstract
With the increasing popularity of electric vehicles and the growing trend of working from home, electricity consumption in the residential sector is expected to continue to grow rapidly over the next few years. As a consequence, short-term residential load forecasting is becoming even more vital for the reliability and sustainability of the smart grid. Although deep learning models have shown impressive success in different areas including short-term electric load forecasting, such models require a large amount of training data. For many
Topics
deep learningknowledge distillationtelecommunications
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@inproceedings{wu2022short, title={Short-term load forecasting with deep boosting transfer regression}, author={Wu, Di and Xu, Yi Tian and Jenkin, Michael and Wang, Ju and Li, Hang and Liu, Xue and Dudek, Gregory}, booktitle={ICC 2022-IEEE International Conference on Communications}, pages={5530--5536}, year={2022}, organization={IEEE} }
Traffic scenario clustering and load balancing with distilled reinforcement learning policies
Li; Jimmy; Di Wu; Yi Tian Xu; Tianyu Li; Seowoo Jang; Xue Liu; Gregory Dudek

2022Proc. IEEE International Conference on Communications (ICC)
Abstract
Abstract
Due to the rapid increase in wireless communication traffic in recent years, load balancing is becoming increasingly important for ensuring the quality of service. However, variations in traffic patterns near different serving base stations make this task challenging. On one hand, crafting a single control policy that performs well across all base station sectors is often difficult. On the other hand, maintaining separate controllers for every sector introduces overhead, and leads to redundancy if some of the sectors experience similar traffic patterns
Topics
knowledge distillationreinforcement learningtelecommunications
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@inproceedings{Li2022, author = {J. Li and D. Wu and Y.T. Xu and T. Li and J. Seowoo and X. Liu and G.L. Dudek}, title = {Traffic scenario clustering and load balancing with distilled reinforcement learning policies}, booktitle = {Proc. IEEE International Conference on Communications (ICC)}, year = {2022}, month = {Apr.}, date = {20}, }
Visuotactile-RL: Learning multimodal manipulation policies with deep reinforcement learning
Hansen; J.; F. Hogan; D. Rivkin; D. Meger; M. Jenkin; G. Dudek

20222022 International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Manipulating objects with dexterity requires timely feedback that simultaneously leverages the senses of vision and touch. In this paper, we focus on the problem setting where both visual and tactile sensors provide pixel-level feedback for Visuotactile reinforcement learning agents. We investigate the challenges associated with multimodal learning and propose several improvements to existing RL methods; including tactile gating, tactile data augmentation, and visual degradation. When compared with visual-only and tactile-only
Topics
human-robot interactiontactile sensing
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@inproceedings{Hansen2022, author = {Hansen, J. and Hogan, F. and Rivkin, D. and Meger, D. and Jenkin, M. and Dudek, G.}, title = {Visuotactile-RL: Learning multimodal manipulation policies with deep reinforcement learning}, booktitle = {2022 International Conference on Robotics and Automation (ICRA)}, year = {2022}, pages = {8298--8304}, doi = {10.1109/ICRA46639.2022.9812019} }
AFB: Improving Communication Load Forecasting Accuracy with Adaptive Feature Boosting
C. Hu; X. Chen; J. Wang; H. Li; J. Kang; Y. T. Xu; X. Liu; D. Wu; S. Jang; G. Dudek

2021in 2021 IEEE Global Communications Conference (GLOBECOM), pp. 1--6, 2021
Abstract
Abstract
AFB: Improving Communication Load Forecasting Accuracy with Adaptive Feature Boosting
Topics
telecommunications
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@misc{afbimprovingcommunicationloadforecasting, author = {C. Hu and X. Chen and J. Wang and H. Li and J. Kang and Y. T. Xu and X. Liu and D. Wu and S. Jang and G. Dudek}, title = {AFB: Improving Communication Load Forecasting Accuracy with Adaptive Feature Boosting}, year = {2021}, booktitle = {in 2021 IEEE Global Communications Conference (GLOBECOM), pp. 1--6, 2021}, }
An Autonomous Probing System for Collecting Measurements at Depth from Small Surface Vehicles
Y. Huang; Y. Yao; J. Hansen; J. Mallette; S. Manjanna; G. Dudek; D. Meger

2021in OCEANS 2021: San Diego--Porto, pp. 1--6, 2021
Abstract
Abstract
An Autonomous Probing System for Collecting Measurements at Depth from Small Surface Vehicles
Topics
underwater robotics
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@misc{anautonomousprobingsystemforcollectingme, author = {Y. Huang and Y. Yao and J. Hansen and J. Mallette and S. Manjanna and G. Dudek and D. Meger}, title = {An Autonomous Probing System for Collecting Measurements at Depth from Small Surface Vehicles}, year = {2021}, journal = {in OCEANS 2021: San Diego--Porto, pp. 1--6, 2021}, }
Average Outward Flux Skeletons for Environment Mapping and Topology Matching
M. Rezanejad; B. Samari; E. Karimi; I. Rekleitis; G. Dudek; K. Siddiqi

2021arXiv preprint arXiv …
Abstract
Abstract
We consider how to directly extract a road map (also known as a topological representation) of an initially-unknown 2-dimensional environment via an online procedure that robustly computes a retraction of its boundaries. In this article, we first present the online construction of a topological map and the implementation of a control law for guiding the robot to the nearest unexplored area, first presented in [1]. The proposed method operates by allowing the robot to localize itself on a partially constructed map, calculate a path to unexplored parts
Topics
complexity boundsenvironment mappinggraph theorylocalizationpath planning
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@misc{averageoutwardfluxskeletonsforenvironmen, author = {M. Rezanejad and B. Samari and E. Karimi and I. Rekleitis and G. Dudek and K. Siddiqi}, title = {Average Outward Flux Skeletons for Environment Mapping and Topology Matching}, year = {2021}, journal = {arXiv preprint arXiv …}, url = {https://arxiv.org/abs/2111.13826}, }
DRIFT-NCRN: A Benchmark Dataset for Drifter Trajectory Prediction
J Hansen; K Virji; T Manderson; D Meger; G Dudek

2021NA
Abstract
Abstract
• Influenced by the complex interactions at the intersection of air and water, the fate of objects floating in the ocean is difficult to predict even a few days into the future • Accurate, long-term predictions of ocean trajectories have many important applications • Search and rescue missions • Get positions of drifters on day 20 and seed particles in those locations • Feed in forecast data for the remaining 10 days • Run the simulation and compare simulated particle trajectories with observed drifter trajectories
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@misc{driftncrnabenchmarkdatasetfordriftertraj, author = {J Hansen and K Virji and T Manderson and D Meger and G Dudek}, title = {DRIFT-NCRN: A Benchmark Dataset for Drifter Trajectory Prediction}, year = {2021}, journal = {NA}, url = {https://www.mcgill.ca/ose/files/ose/khalil_poster.pdf}, }
Hierarchical policy learning for hybrid communication load balancing
Kang; J.; X. Chen; D. Wu; Y.T. Xu; X. Liu; G. Dudek; T. Lee; I. Park

2021Proc. IEEE International Conference on Communications (ICC)
Abstract
Abstract
Due to the uneven demographic distribution and people's daily activities, communication systems usually experience highly imbalanced load across different cells. This imbalance leads to unsatisfied users in the congested cells and under-utilized resources in the less-loaded cells. To deal with this issue, existing work migrates the load from heavily loaded cells to lightly loaded cells, by either handing over active mode User Equipment (UEs) to other serving cells, or re-selecting the camping cells for idle mode UEs. In this paper, we
Topics
knowledge distillationlocalizationreinforcement learningtelecommunications
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@inproceedings{Kang2021, author = {J. Kang and X. Chen and D. Wu and Y.T. Xu and X. Liu and G. Dudek and T. Lee and I. Park}, title = {Hierarchical policy learning for hybrid communication load balancing}, booktitle = {Proc. IEEE International Conference on Communications (ICC)}, year = {2021}, pages = {6}, doi = {10.1109/ICC42927.2021.9500379} }

Latent Attention Augmentation for Robust Autonomous Driving Policies

R. Cheng; C. Agia; F. Shkurti; D. Meger; G. Dudek

2021in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021

Abstract

Latent Attention Augmentation for Robust Autonomous Driving Policies

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@misc{latentattentionaugmentationforrobustauto,
  author = {R. Cheng and C. Agia and F. Shkurti and D. Meger and G. Dudek},
  title = {Latent Attention Augmentation for Robust Autonomous Driving Policies},
  year = {2021},
  booktitle = {in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021},
}

Learning Assisted Identification of Scenarios Where Network Optimization Algorithms Under-Perform
Rivkin, Dmitriy; Meger, David; Wu, Di; Chen, Xi; Liu, ue; Dudek, Gregory

2021Proc. IEEE Global Communications Conference (Globecom 2021)
Abstract
Abstract
We present a generative adversarial method that uses deep learning to identify network load traffic conditions in which network optimization algorithms under-perform other known algorithms: the Deep Convolutional Failure Generator (DCFG). The spatial distribution of network load presents challenges for network operators for tasks such as load balancing, in which a network optimizer attempts to maintain high quality communication while at the same time abiding capacity constraints. Testing a network optimizer for all possible load
Topics
deep learninggenerative aiknowledge distillationtelecommunications
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@inproceedings{rivkin2021learning, title={Learning Assisted Identification of Scenarios Where Network Optimization Algorithms Under-Perform}, author={Rivkin, Dmitriy and Meger, David and Wu, Di and Chen, Xi and Liu, ue and Dudek, Gregory}, booktitle={Proc. IEEE Global Communications Conference (Globecom 2021)}, pages={6}, year={2021}, address={Madrid, Spain}, month={Dec} }

Learning goal conditioned socially compliant navigation from demonstration using risk-based features

Konar; A.; B. H. Baghi; G. Dudek.

2021IEEE Robotics and Automation Letters

Abstract

One of the main challenges of operating mobile robots in social environments is the safe and fluid navigation therein, specifically the ability to share a space with other human inhabitants by complying with the explicit and implicit rules that we humans follow during navigation. While these rules come naturally to us, they resist simple and explicit definitions. In this letter, we present a learning-based solution to address the question of socially compliant navigation, which is to navigate while maintaining adherence to the navigational

Topics

complexity boundsgraph theoryhuman-robot interactionlocalizationslamtelecommunicationsunderwater robotics

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@article{konar2021learning,
 abstract = {One of the main challenges of operating mobile robots in social environments is the safe and fluid navigation therein, specifically the ability to share a space with other human inhabitants by complying with the explicit and implicit rules that we humans follow during navigation. While these rules come naturally to us, they resist simple and explicit definitions. In this letter, we present a learning-based solution to address the question of socially compliant navigation, which is to navigate while maintaining adherence to the navigational},
 author = {Konar, Abhisek and Baghi, Bobak H and Dudek, Gregory},
 journal = {IEEE Robotics and Automation Letters},
 number = {2},
 pages = {651--658},
 pub_year = {2021},
 publisher = {IEEE},
 title = {Learning goal conditioned socially compliant navigation from demonstration using risk-based features},
 venue = {IEEE Robotics and Automation …},
 volume = {6}
}

Learning goal conditioned socially compliant navigation from demonstration using risk-based features

Konar; A.; B. H. Baghi; G. Dudek

2021IEEE Robotics and Automation Letters

Abstract

Topics

complexity boundsgraph theoryhuman-robot interactionlocalizationslamtelecommunicationsunderwater robotics

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@article{konar2021learning,
 abstract = {One of the main challenges of operating mobile robots in social environments is the safe and fluid navigation therein, specifically the ability to share a space with other human inhabitants by complying with the explicit and implicit rules that we humans follow during navigation. While these rules come naturally to us, they resist simple and explicit definitions. In this letter, we present a learning-based solution to address the question of socially compliant navigation, which is to navigate while maintaining adherence to the navigational},
 author = {Konar, Abhisek and Baghi, Bobak H and Dudek, Gregory},
 journal = {IEEE Robotics and Automation Letters},
 number = {2},
 pages = {651--658},
 pub_year = {2021},
 publisher = {IEEE},
 title = {Learning goal conditioned socially compliant navigation from demonstration using risk-based features},
 venue = {IEEE Robotics and Automation …},
 volume = {6}
}

Learning Intuitive Physics with Multimodal Generative Models
Rezaei-Shoshtari; S.; F.R. Hogan; M. Jenkin; D. Meger; G. Dudek

2021Proceedings of the AAAI Conference on Artificial Intelligence
Abstract
Abstract
Predicting the future interaction of objects when they come into contact with their environment is key for autonomous agents to take intelligent and anticipatory actions. This paper presents a perception framework that fuses visual and tactile feedback to make predictions about the expected motion of objects in dynamic scenes. Visual information captures object properties such as 3D shape and location, while tactile information provides critical cues about interaction forces and resulting object motion when it makes contact with
Topics
deep learninglocalizationobject recognitionreinforcement learningslamtactile sensingvariational methods
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@inproceedings{Rezaei-Shoshtari2021, author = {S. Rezaei-Shoshtari and F. R. Hogan and M. Jenkin and D. Meger and G. Dudek}, title = {Learning Intuitive Physics with Multimodal Generative Models}, booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence}, year = {2021}, month = {Feb}, volume = {2101}, note = {preprint as doi:arXiv:2101.04454}, url = {http://adsabs.harvard.edu/abs/2021arXiv210104454R} }
Load Balancing for Communication Networks via Data-Efficient Deep Reinforcement Learning
Di Wu; Jikun Kang; Yi Tian Xu; Hang Li; Jimmy Li; Xi Chen; Dmitriy Rivkin; Michael Jenkin; Taeseop Lee; Intaik Park; Xue Liu; Gregory Dudek

2021Proc. IEEE Global Communications Conference (Globecom 2021)
Abstract
Abstract
Within a cellular network, load balancing between different cells is of critical importance to network performance and quality of service. Most existing load balancing algorithms are manually designed and tuned rule-based methods where near-optimality is almost impossible to achieve. These rule-based meth-ods are difficult to adapt quickly to traffic changes in real-world environments. Given the success of Reinforcement Learning (RL) algorithms in many application domains, there have been a number of efforts to tackle load
Topics
knowledge distillationreinforcement learningtelecommunications
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@inproceedings{wu2021load, author = {Di Wu and Jikun Kang and Yi Tian Xu and Hang Li and Jimmy Li and Xi Chen and Dmitriy Rivkin and Michael Jenkin and Taeseop Lee and Intaik Park and Xue Liu and Gregory Dudek}, title = {Load Balancing for Communication Networks via Data-Efficient Deep Reinforcement Learning}, booktitle = {Proc. IEEE Global Communications Conference (Globecom 2021)}, year = {2021}, address = {Madrid, Spain}, month = {Dec.}, pages = {6} }
Multimodal dynamics modeling for off-road autonomous vehicles
Tremblay; J.-F.; T. Manderson; A. Noca; G. Dudek; D. Meger

20212021 IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Dynamics modeling in outdoor and unstructured environments is difficult because different elements in the environment interact with the robot in ways that can be hard to predict. Leveraging multiple sensors to perceive maximal information about the robot's environment is thus crucial when building a model to perform predictions about the robot's dynamics with the goal of doing motion planning. We design a model capable of long-horizon motion predictions, leveraging vision, lidar and proprioception, which is robust to arbitrarily missing
Topics
path planning
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@inproceedings{Tremblay2021, author = {J.-F. Tremblay and T. Manderson and A. Noca and G. Dudek and D. Meger}, title = {Multimodal dynamics modeling for off-road autonomous vehicles}, booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)}, year = {2021}, pages = {1796--1802}, doi = {10.1109/ICRA48506.2021.9561910} }
One for All: Traffic Prediction at Heterogeneous 5G Edge with Data-Efficient Transfer Learning
Xi Chen; Ju Wang; Hang Li; Yi Tian Xu; Di Wu; Xue Liu; Gregory Dudek; Taeseop Lee; Intaik Park

2021Proc. IEEE Global Communications Conference (Globecom 2021)Best paper award
Abstract
Abstract
By placing the computing, storage and networking resources close to the end users, distributed edge computing greatly benefits the performance of 5G communication systems. However, as a tradeoff, resources on the edge are usually limited and imbalanced among the heterogeneous edge nodes. To overcome this drawback, this paper proposes a Transfer Learning based Prediction (TLP) framework that allows the edge nodes to share their resources and data in an efficient manner. In particular, the TLP framework focuses on the
Topics
knowledge distillationtelecommunications
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@inproceedings{chen2021one, author = {Xi Chen and Ju Wang and Hang Li and Yi Tian Xu and Di Wu and Xue Liu and Gregory Dudek and Taeseop Lee and Intaik Park}, title = {One for All: Traffic Prediction at Heterogeneous 5G Edge with Data-Efficient Transfer Learning}, booktitle = {Proc. IEEE Global Communications Conference (Globecom 2021)}, year = {2021}, address = {Madrid, Spain}, month = {Dec.}, pages = {6}, note = {Best paper award} }
Optimizing Cellular Networks via Continuously Moving Base Stations on Road Networks
Girdhar; Y.; D. Rivkin; D. Wu; M. Jenkin; X. Liu; G. Dudek

20212021 IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Although existing cellular network base stations are typically immobile, the recent development of small form factor base stations and self driving cars has enabled the possibility of deploying a team of continuously moving base stations that can reorganize the network infrastructure to adapt to changing network traffic usage patterns. Given such a system of mobile base stations (MBSes) that can freely move on the road, how should their path be planned in an effort to optimize the experience of the users? This paper addresses
Topics
adaptive controlcomplexity boundspath planningtelecommunications
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@inproceedings{Girdhar2021, author = {Y. Girdhar and D. Rivkin and D. Wu and M. Jenkin and X. Liu and G. Dudek}, title = {Optimizing Cellular Networks via Continuously Moving Base Stations on Road Networks}, booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)}, year = {2021}, pages = {4020--4025}, doi = {10/gntw2n} }
Sample Efficient Social Navigation Using Inverse Reinforcement Learning
B. H. Baghi; G. Dudek

2021arXiv preprint arXiv:2106.10318, 2021
Abstract
Abstract
Sample Efficient Social Navigation Using Inverse Reinforcement Learning
Topics
inverse reinforcement learningreinforcement learning
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@misc{sampleefficientsocialnavigationusinginve, author = {B. H. Baghi and G. Dudek}, title = {Sample Efficient Social Navigation Using Inverse Reinforcement Learning}, year = {2021}, journal = {arXiv preprint arXiv:2106.10318, 2021}, }

Scalable Multi-Robot System for Non-myopic Spatial Sampling

Manjanna; S.; M.A. Hsieh; G. Dudek

2021arXiv:2105.10018 [cs]

Abstract

Scalable Multi-Robot System for Non-myopic Spatial Sampling

Topics

adaptive samplingcooperative localizationlocalizationslam

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@article{Manjanna2021,
  author    = {S. Manjanna and M. A. Hsieh and G. Dudek},
  title     = {Scalable Multi-Robot System for Non-myopic Spatial Sampling},
  journal   = {arXiv:2105.10018 [cs]},
  year      = {2021},
  month     = {Oct.},
  note      = {Accessed: Dec. 21, 2021},
  url       = {http://arxiv.org/abs/2105.10018}
}

Scalable Multi-Robot System for Non-myopic Spatial Sampling

Manjanna; S.; M.A. Hsieh; G. Dudek

2021arXiv:2105.10018 [cs]

Abstract

Scalable Multi-Robot System for Non-myopic Spatial Sampling

Topics

adaptive samplingcooperative localizationlocalizationslam

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@article{Manjanna2021,
  author    = {S. Manjanna and M. A. Hsieh and G. Dudek},
  title     = {Scalable Multi-Robot System for Non-myopic Spatial Sampling},
  journal   = {arXiv:2105.10018 [cs]},
  year      = {2021},
  month     = {Oct.},
  note      = {Accessed: Dec. 21, 2021},
  url       = {http://arxiv.org/abs/2105.10018}
}

Scale-invariant localization using quasi-semantic object landmarks
Holliday; A.; G. Dudek

2021Autonomous Robots
Abstract
Abstract
This work presents Object Landmarks, a new type of visual feature designed for visual localization over major changes in distance and scale. An Object Landmark consists of a bounding box b defining an object, a descriptor q of that object produced by a Convolutional Neural Network, and a set of classical point features within b. We evaluate Object Landmarks on visual odometry and place-recognition tasks, and compare them against several modern approaches. We find that Object Landmarks enable superior
Topics
landmark-based methodslocalizationplace recognitionslam
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@misc{scaleinvariantlocalizationusingquasisema, author = {Holliday and A. and G. Dudek}, title = {Scale-invariant localization using quasi-semantic object landmarks}, year = {2021}, journal = {Autonomous Robots}, url = {https://link.springer.com/article/10.1007/s10514-021-09973-w}, }
Seeing Through your Skin: Recognizing Objects with a Novel Visuotactile Sensor
Hogan; F.R.; M. Jenkin; S. Rezaei-Shoshtari; Y. Girdhar; D. Meger; G. Dudek

2021Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision
Abstract
Abstract
We introduce a new class of vision-based sensor and associated algorithmic processes that combine visual imaging with high-resolution tactile sending, all in a uniform hardware and computational architecture. We demonstrate the sensor's efficacy for both multi-modal object recognition and metrology. Object recognition is typically formulated as an unimodal task, but by combining two sensor modalities we show that we can achieve several significant performance improvements. This sensor, named the See-Through-your-Skin sensor (STS)
Topics
deep learningobject recognitiontexture
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@inproceedings{hogan2021seeing, title={Seeing Through your Skin: Recognizing Objects with a Novel Visuotactile Sensor}, author={Hogan, F.R. and Jenkin, M. and Rezaei-Shoshtari, S. and Girdhar, Y. and Meger, D. and Dudek, G.}, booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision}, pages={1218--1227}, year={2021} }
Toy Story1 Method for Multi-Policy Social Navigation
Konar; A.; B.H. Baghi; F.R. Hogan; G. Dudek

2021RSS Workshop on Social Robot Navigation
Abstract
Abstract
In this work, we present a method for effective social navigation by selecting navigation policies based on local social context. Learning robotic navigation policies that are consistent with inferred social norms is challenging as these norms are often subjective, culturally dependent, task specific, and context sensitive. While learning-based approaches to social navigation have shown success, they must also be able to compete with established classical algorithms that confer theoretical and practical advantages in simpler
Topics
inverse reinforcement learningreinforcement learning
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@inproceedings{konar2021toy, author = {Konar, A. and Baghi, B.H. and Hogan, F.R. and Dudek, G.}, title = {Toy Story1 Method for Multi-Policy Social Navigation}, booktitle = {RSS Workshop on Social Robot Navigation}, pages = {5}, year = {2021}, month = {Jul} }
Trajectory-constrained deep latent visual attention for improved local planning in presence of heterogeneous terrain
S. Wapnick; T. Manderson; D. Meger; G. Dudek

20212021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We present a reward-predictive, model-based learning method featuring trajectory-constrained visual attention for use in mapless, local visual navigation tasks. Our method learns to place visual attention at locations in latent image space which follow trajectories caused by vehicle control actions to later enhance predictive accuracy during planning. Our attention model is jointly optimized by the task-specific loss and additional trajectory-constraint loss, allowing adaptability yet encouraging a regularized structure for improved
Topics
deep learningpath planningreinforcement learning
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@misc{trajectoryconstraineddeeplatentvisualatt, author = {S. Wapnick and T. Manderson and D. Meger and G. Dudek}, title = {Trajectory-constrained deep latent visual attention for improved local planning in presence of heterogeneous terrain}, year = {2021}, booktitle = {2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, url = {https://ieeexplore.ieee.org/abstract/document/9636422/}, }
UWB-Assisted Fast mmWave Beam Alignment
Wang; J.; X. Chen; X. Liu; G. Dudek

2021ICC 2021 - IEEE International Conference on Communications
Abstract
Abstract
Due to their large bandwidth and impressive data speed, millimeter-wave (mmWave) radios are expected to play a key role in the 5G and beyond (eg, 6G) communication networks. Yet, to release mmWave's true power, the highly directional mmWave beams need to be aligned perfectly. Most existing beam alignment methods adopt an exhaustive or semi-exhaustive space scanning, which introduces up to seconds of delays. To eliminate the need of a complex space scanning, this paper presents an Ultra-wideband (UWB)-assisted mmWave
Topics
telecommunications
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@inproceedings{wang2021uwb, author = {Wang, J. and Chen, X. and Liu, X. and Dudek, G.}, title = {UWB-Assisted Fast mmWave Beam Alignment}, booktitle = {ICC 2021 - IEEE International Conference on Communications}, year = {2021}, pages = {1--6}, doi = {10.1109/ICC42927.2021.9500352}, month = {Jun.} }
Capturing attention with wind
Friedman; N.; D. Goedicke; V. Zhang; D. Rivkin; M. Jenkin; Z. Degutyte; A. Astell; X. Liu; G. Dudek

2020Workshop on Approaches to Advance Physical Human-Robot Interaction (AVHC)
Abstract
Abstract
Having a robot interact with people in a shared environment is complex. Both running into humans and loud audio warnings are inappropriate. Visual signalling may be appropriate but is only effective if the humans are looking at/attending to the robot vehicle. Are there effective and socially acceptable mechanisms that a robot can exploit to capture the attention of humans in a shared environment? Here we explore the potential of using controlled blasts of wind (haptic air) to capture attention in a socially acceptable manner.
Topics
gesture-based interactionhuman-robot interactiontelecommunications
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@inproceedings{Friedman2020, author = {Friedman, N. and Goedicke, D. and Zhang, V. and Rivkin, D. and Jenkin, M. and Degutyte, Z. and Astell, A. and Liu, X. and Dudek, G.}, title = {Capturing attention with wind}, booktitle = {Workshop on Approaches to Advance Physical Human-Robot Interaction (AVHC)}, year = {2020}, month = {May}, pages = {2}, url = {https://vgrserver.eecs.yorku.ca/~jenkin/papers/2020/2020ICRAWorkshop.pdf} }
Collaborative Human-Robot Exploration for Marine Environments
Juan Camilo Gamboa Higuera; Travis Manderson; Karim Koreitem; Wei-Di Chang; Florian Shkurti; David Meger; Gregory Dudek

2020RSS '20 Workshop on Assistive and Collaborative Robotics: Decoding Intent
Abstract
Abstract
Collaborative Human-Robot Exploration for Marine Environments
Topics
exploration strategieshuman-robot interactionunderwater robotics
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@inproceedings{gamboa2020collaborative, author = {Juan Camilo Gamboa Higuera and Travis Manderson and Karim Koreitem and Wei-Di Chang and Florian Shkurti and David Meger and Gregory Dudek}, title = {Collaborative Human-Robot Exploration for Marine Environments}, booktitle = {RSS '20 Workshop on Assistive and Collaborative Robotics: Decoding Intent}, year = {2020} }
DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization
Joshi; Bharat; Md Modasshir; Travis Manderson; Hunter Damron; Marios Xanthidis; Alberto Quattrini Li; Ioannis Rekleitis; Gregory Dudek.

2020Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)
Abstract
Abstract
In this paper, we propose a real-time deep learning approach for determining the 6D relative pose of Autonomous Underwater Vehicles (AUV) from a single image. A team of autonomous robots localizing themselves in a communication-constrained underwater environment is essential for many applications such as underwater exploration, mapping, multi-robot convoying, and other multi-robot tasks. Due to the profound difficulty of collecting ground truth images with accurate 6D poses underwater, this work utilizes rendered images
Topics
cooperative localizationdeep learninglocalizationrobotic collectivesslamunderwater navigationunderwater robotics
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@inproceedings{joshi2020deepurl, title={DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization}, author={Joshi, Bharat and Modasshir, Md and Manderson, Travis and Damron, Hunter and Xanthidis, Marios and Quattrini Li, Alberto and Rekleitis, Ioannis and Dudek, Gregory}, booktitle={Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS)}, year={2020} }
Depth Prediction for Monocular Direct Visual Odometry
Cheng; Ran; Christopher Agia; David Meger; Gregory Dudek.

20202020 17th Conference on Computer and Robot Vision (CRV)
Abstract
Abstract
Depth prediction from monocular images with deep CNNs is a topic of increasing interest to the community. Advances have lead to models capable of predicting disparity maps with consistent scale, which are an acceptable prior for gradient-based direct methods. With this in consideration, we exploit depth prediction as a candidate prior for the coarse initialization, tracking, and marginalization steps of the direct visual odometry system, enabling the second-order optimizer to converge faster into a precise global minimum. In addition, the
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@inproceedings{Cheng2020, author = {Ran Cheng and Christopher Agia and David Meger and Gregory Dudek}, title = {Depth Prediction for Monocular Direct Visual Odometry}, booktitle = {2020 17th Conference on Computer and Robot Vision (CRV)}, pages = {70--77}, year = {2020}, publisher = {IEEE Computer Society} }
Dynamic Planning of Redundant Robots within a Set-Based Task-Priority Inverse Kinematics Framework
Di Vito; Daniele; Mathieux Bergeron; David Meger; Gregory Dudek; Gianluca Antonelli.

20202020 IEEE Conference on Control Technology and Applications (CCTA)
Abstract
Abstract
This work presents the dynamic planning of redundant robots by merging a global and local planner. The global planner is implemented as a sampling-based algorithm which works in the reduced-dimensionality of the robot workspace applying the Cartesian constraints only. The output trajectory is then checked within a framework of set-based task priority inverse kinematics verifying the fulfillment of the other task constraints. The inverse kinematics framework is used also in real-time as local motion control to ensure a reactive behaviour to
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@inproceedings{di2020dynamic, title={Dynamic Planning of Redundant Robots within a Set-Based Task-Priority Inverse Kinematics Framework}, author={Di Vito, Daniele and Mathieux Bergeron, David Meger, Gregory Dudek, and Gianluca Antonelli}, booktitle={2020 IEEE Conference on Control Technology and Applications (CCTA)}, pages={549--554}, year={2020}, organization={IEEE} }
FiDo: Ubiquitous Fine-Grained WiFi-Based Localization for Unlabelled Users via Domain Adaptation
Chen; Xi; Li; Hang; Zhou; Chenyi; Liu; Xue; Wu; Di; Dudek; Gregory.

2020Proceedings of The Web Conference 2020 (WWW '20)
Abstract
Abstract
To fully support the emerging location-aware applications, location information with meter-level resolution (or even higher) is required anytime and anywhere. Unfortunately, most of the current location sources (eg, GPS and check-in data) either are unavailable indoor or provide only house-level resolutions. To fill the gap, this paper utilizes the ubiquitous WiFi signals to establish a (sub) meter-level localization system, which employs WiFi propagation characteristics as location fingerprints. However, an unsolved issue of these WiFi
Topics
domain adaptationlocalizationtelecommunications
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@inproceedings{Chen2020FiDo, author = {Xi Chen and Hang Li and Chenyi Zhou and Xue Liu and Di Wu and Gregory Dudek}, title = {FiDo: Ubiquitous Fine-Grained WiFi-Based Localization for Unlabelled Users via Domain Adaptation}, booktitle = {Proceedings of The Web Conference 2020 (WWW '20)}, pages = {23--33}, year = {2020}, location = {Taipei, Taiwan}, publisher = {Association for Computing Machinery}, doi = {10.1145/3366423.3380091} }
Learning Domain Randomization Distributions for Training Robust Locomotion Policies
M. Mozifian, J. C. Gamboa Higuera, D. Meger,; G. Dudek

2020in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
Abstract
Abstract
Learning Domain Randomization Distributions for Training Robust Locomotion Policies
Topics
reinforcement learningwalking robots
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@misc{learningdomainrandomizationdistributions, author = {M. Mozifian, J. C. Gamboa Higuera, D. Meger, and G. Dudek}, title = {Learning Domain Randomization Distributions for Training Robust Locomotion Policies}, year = {2020}, booktitle = {in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020}, }
Learning Domain Randomization Distributions for Training Robust Locomotion Policies
M. Mozifian, J. C. Gamboa Higuera, D. Meger,; G. Dudek

2020in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
Abstract
Abstract
Learning Domain Randomization Distributions for Training Robust Locomotion Policies
Topics
reinforcement learningwalking robots
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@misc{learningdomainrandomizationdistributions, author = {M. Mozifian, J. C. Gamboa Higuera, D. Meger, and G. Dudek}, title = {Learning Domain Randomization Distributions for Training Robust Locomotion Policies}, year = {2020}, booktitle = {in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020}, }
Learning to Drive Off-Road on Smooth Terrains in Unstructured Environments Using an Onboard Camera and Sparse Aerial Images
Manderson, Travis; Wapnick, Stefan; Meger, Dave; Dudek, Gregory

2020Proceedings of the 2020 IEEE International Conference on Robotics and Automation
Abstract
Abstract
We present a method for learning to drive on smooth terrain while simultaneously avoiding collisions in challenging off-road and unstructured outdoor environments using only visual inputs. Our approach applies a hybrid model-based and model-free reinforcement learning method that is entirely self-supervised in labeling terrain roughness and collisions using on-board sensors. Notably, we provide both first-person and overhead aerial image inputs to our model. We nd that the fusion of these complementary inputs improves planning foresight
Topics
landmark-based methodsreinforcement learning
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@inproceedings{manderson2020learning, title={Learning to Drive Off-Road on Smooth Terrains in Unstructured Environments Using an Onboard Camera and Sparse Aerial Images}, author={Manderson, Travis and Wapnick, Stefan and Meger, Dave and Dudek, Gregory}, booktitle={Proceedings of the 2020 IEEE International Conference on Robotics and Automation}, year={2020} }
Learning to Drive Off-Road on Smooth Terrains in Unstructured Environments Using an Onboard Camera and Sparse Aerial Images
Manderson; Travis; Stefan Wapnick; Dave Meger; Gregory Dudek.

2020Proceedings of the 2020 IEEE International Conference on Robotics and Automation
Abstract
Abstract
We present a method for learning to drive on smooth terrain while simultaneously avoiding collisions in challenging off-road and unstructured outdoor environments using only visual inputs. Our approach applies a hybrid model-based and model-free reinforcement learning method that is entirely self-supervised in labeling terrain roughness and collisions using on-board sensors. Notably, we provide both first-person and overhead aerial image inputs to our model. We nd that the fusion of these complementary inputs improves planning foresight
Topics
landmark-based methodsreinforcement learning
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@inproceedings{manderson2020learning, title={Learning to Drive Off-Road on Smooth Terrains in Unstructured Environments Using an Onboard Camera and Sparse Aerial Images}, author={Manderson, Travis and Wapnick, Stefan and Meger, Dave and Dudek, Gregory}, booktitle={Proceedings of the 2020 IEEE International Conference on Robotics and Automation}, year={2020} }
One-Shot Informed Robotic Visual Search in the Wild
Koreitem; Karim; Florian Shkurti; Travis Manderson; Wei-Di Chang; Juan Camilo Gamboa Higuera; Gregory Dudek.

2020Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS 2020)
Abstract
Abstract
We consider the task of underwater robot navigation for the purpose of collecting scientifically relevant video data for environmental monitoring. The majority of field robots that currently perform monitoring tasks in unstructured natural environments navigate via path-tracking a pre-specified sequence of waypoints. Although this navigation method is often necessary, it is limiting because the robot does not have a model of what the scientist deems to be relevant visual observations. Thus, the robot can neither visually search for
Topics
exploration strategiespath planningunderwater navigationunderwater robotics
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@inproceedings{koreitem2020one, title={One-Shot Informed Robotic Visual Search in the Wild}, author={Koreitem, Karim and Shkurti, Florian and Manderson, Travis and Chang, Wei-Di and Gamboa Higuera, Juan Camilo and Dudek, Gregory}, booktitle={Proc. IEEE/RSJ International Conference on Robotics and Systems (IROS 2020)}, year={2020} }
Out of my way! Exploring Different Modalities for Robots to Ask People to Move Out of the Way
Friedman; N.; D. Goedicke; V. Zhang; D. Rivkin; M. Jenkin; Z. Degutyte; A. Astell; X. Liu; G. Dudek

2020Workshop on Active Vision and Perception in Human(-Robot) Collaboration. Held in conjunction with the 29th IEEE Int. Conf. on Robot and Human Interactive CommunicationBest paper award
Abstract
Abstract
To navigate politely through social spaces, a mobile robot needs to communicate successfully with human bystanders. What is the best way for a robot to attract attention in a socially acceptable manner to communicate its intent to others in a shared space? Through a series of in-the-wild experiments, we measured the social appropriateness and effectiveness of different modalities for robots to communicate to people their intended movement, using combinations of visual text, audio and haptic cues. Using multiple
Topics
gesture-based interactionhuman-robot interaction
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@inproceedings{Friedman2020, author = {Friedman, N. and Goedicke, D. and Zhang, V. and Rivkin, D. and Jenkin, M. and Degutyte, Z. and Astell, A. and Liu, X. and Dudek, G.}, title = {Out of my way! Exploring Different Modalities for Robots to Ask People to Move Out of the Way}, booktitle = {Workshop on Active Vision and Perception in Human(-Robot) Collaboration. Held in conjunction with the 29th IEEE Int. Conf. on Robot and Human Interactive Communication}, pages = {9}, year = {2020}, note = {Best paper award}, url = {https://vgrserver.eecs.yorku.ca/~jenkin/papers/2020/AVHRC2020-out-of-my-way.pdf} }
Pre-Trained CNNs as Visual Feature Extractors: A Broad Evaluation
Holliday; Andrew; Gregory Dudek.

20202020 17th Conference on Computer and Robot Vision (CRV)
Abstract
Abstract
In this work, we perform a wide-ranging evaluation of Convolutional Neural Networks (CNNs) as feature extractors for matching visual features under large changes in appearance, perspective, and visual scale. Our evaluation covers 82 different layers from twelve different CNN architectures belonging to four families: AlexNets, VGG Nets, ResNets, and DenseNets. To our knowledge, this is the most comprehensive analysis of its kind in the literature. We find that the intermediate layers of DenseNets serve as the best feature
Topics
image matching
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@inproceedings{holliday2020pre, title={Pre-Trained CNNs as Visual Feature Extractors: A Broad Evaluation}, author={Holliday, Andrew and Dudek, Gregory}, booktitle={2020 17th Conference on Computer and Robot Vision (CRV)}, pages={78--84}, year={2020}, organization={IEEE} }
PresSense: Passive Respiration Sensing via Ambient WiFi Signals in Noisy Environments
Xu; Y.T.; X. Chen; X. Liu; D. Meger; G. Dudek

20202020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Passive sensing with ambient WiFi signals is a promising technique that will enable new types of human-robot interactions while preserving users' privacy. Here, we present PresSense, a system for human respiration sensing in noisy environments. Unlike existing WiFi-based respiration sensors, we employ a human presence detector, improving the robustness in scenarios where no human is present in an Area Of Interest (AOI). We also integrate our novel feature, Peak Distance Histogram (PDH), with other classic WiFi features
Topics
human-robot interaction
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@inproceedings{Xu2020, author = {Y.T. Xu and X. Chen and X. Liu and D. Meger and G. Dudek}, title = {PresSense: Passive Respiration Sensing via Ambient WiFi Signals in Noisy Environments}, booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2020}, month = {Oct}, pages = {4032--4039}, doi = {10/gntw35} }
Seeing Through Your Skin: A Novel Visuo-Tactile Sensor for Robotic Manipulation
Hogan; F. R.; S. Rezaei-Shoshtari; M. Jenkin; Y. Girdhar; D. Meger; G. Dudek.

2020Visual Learning and Reasoning for Robotic Manipulation (Workshop of RSS 2020)
Abstract
Abstract
Seeing Through Your Skin: A Novel Visuo-Tactile Sensor for Robotic Manipulation
Topics
human-robot interactionobject recognitiontactile sensingtexture
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@inproceedings{hogan2020seeing, title={Seeing Through Your Skin: A Novel Visuo-Tactile Sensor for Robotic Manipulation}, author={Hogan, F. R. and Rezaei-Shoshtari, S. and Jenkin, M. and Girdhar, Y. and Meger, D. and Dudek, G.}, booktitle={Visual Learning and Reasoning for Robotic Manipulation (Workshop of RSS 2020)}, year={2020}, address={Corvallis, Oregon, USA} }
Self-Supervised, Goal-Conditioned Policies for Navigation in Unstructured Environments
Manderson; Travis; Juan Camilo Gamboa Higuera; Stefan Wapnick; Jean-Francois Tremblay; Florian Shkurti; David Meger; Gregory Dudek.

2020Robotics Science and Systems (RSS) Workshop on Self-Supervised Robot LearningBest Paper Award
Abstract
Abstract
Self-Supervised, Goal-Conditioned Policies for Navigation in Unstructured Environments
Topics
complexity boundsgraph theorylocalizationreinforcement learningslamunderwater robotics
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@inproceedings{manderson2020self, title={Self-Supervised, Goal-Conditioned Policies for Navigation in Unstructured Environments}, author={Manderson, Travis and Gamboa Higuera, Juan Camilo and Wapnick, Stefan and Tremblay, Jean-Francois and Shkurti, Florian and Meger, David and Dudek, Gregory}, booktitle={Robotics Science and Systems (RSS) Workshop on Self-Supervised Robot Learning}, year={2020}, note={Best Paper Award} }

The Answer Is Blowing in the Wind: Directed Air Flow for Socially-acceptable Human-Robot Interaction.

V Zhang; N Friedman; D Goedicke; D Rivkin; M Jenkin

2020NA

Abstract

Topics

human-robot interactiontactile sensing

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@misc{theanswerisblowinginthewinddirectedairfl,
  author = {V Zhang and N Friedman and D Goedicke and D Rivkin and M Jenkin},
  title = {The Answer Is Blowing in the Wind: Directed Air Flow for Socially-acceptable Human-Robot Interaction.},
  year = {2020},
  journal = {NA},
}

View-Invariant Loop Closure with Oriented Semantic Landmarks
Jimmy; Karim Koreitem; David Meger; Gregory Dudek.

20202020 IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Recent work on semantic simultaneous localization and mapping (SLAM) have shown the utility of natural objects as landmarks for improving localization accuracy and robustness. In this paper we present a monocular semantic SLAM system that uses object identity and inter-object geometry for view-invariant loop detection and drift correction. Our system's ability to recognize an area of the scene even under large changes in viewing direction allows it to surpass the mapping accuracy of ORB-SLAM, which uses only local appearance-based
Topics
landmark-based methodsobject recognitionplace recognitionslam
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@inproceedings{jimmy2020view, title={View-Invariant Loop Closure with Oriented Semantic Landmarks}, author={Jimmy, Karim Koreitem and Meger, David and Dudek, Gregory}, booktitle={2020 IEEE International Conference on Robotics and Automation (ICRA)}, pages={7943--7949}, year={2020}, organization={IEEE} }
Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles
Manderson; Travis; Juan Camilo Gamboa Higuera; Stefan Wapnick; Jean-Francois Tremblay; Florian Shkurti; David Meger; Gregory Dudek.

2020Proceeding of Robotics Science and Systems
Abstract
Abstract
We present Nav2Goal, a data-efficient and end-to-end learning method for goal-conditioned visual navigation. Our technique is used to train a navigation policy that enables a robot to navigate close to sparse geographic waypoints provided by a user without any prior map, all while avoiding obstacles and choosing paths that cover user-informed regions of interest. Our approach is based on recent advances in conditional imitation learning. General-purpose, safe and informative actions are demonstrated by a human expert. The learned
Topics
complexity boundscoral reef mappingexploration strategiesgenerative aigraph theorylocalizationslamunderwater navigationunderwater robotics
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@inproceedings{manderson2020vision, title={Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles}, author={Manderson, Travis and Gamboa Higuera, Juan Camilo and Wapnick, Stefan and Tremblay, Jean-Francois and Shkurti, Florian and Meger, David and Dudek, Gregory}, booktitle={Proceeding of Robotics Science and Systems}, volume={16}, year={2020} }

Detecting GAN Generated Errors

X. Zhu; F. Che; T. Yang; T. Yu; D. Meger; G. Dudek

2019arXiv preprint arXiv:1912.00527, 2019

Abstract

Detecting GAN Generated Errors

Topics

anomaly detectiongenerative ai

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@misc{detectinggangeneratederrors2019,
  author = {X. Zhu and F. Che and T. Yang and T. Yu and D. Meger and G. Dudek},
  title = {Detecting GAN Generated Errors},
  year = {2019},
  journal = {arXiv preprint arXiv:1912.00527, 2019},
}

EnviroNet: ImageNet Analog for Environment and Global AI Challenge
Dudek; Gregory; Lucas Joppa; Valliappa Lakshmanan; Vipin Kumar; Surya Karthik Mukkavilli.

201999th American Meteorological Society Annual Meeting
Abstract
Abstract
99th American Meteorological Society Annual Meeting
Topics
anomaly detectionbayesian inferencecomplexity boundscooperative localizationcoral reef mappingdeep learningdomain adaptationgenerative aihuman-robot interactiontelecommunicationsunderwater robotics
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@inproceedings{dudek2019environet, title={EnviroNet: ImageNet Analog for Environment and Global AI Challenge}, author={Dudek, Gregory and Joppa, Lucas and Lakshmanan, Valliappa and Kumar, Vipin and Mukkavilli, Surya Karthik}, booktitle={99th American Meteorological Society Annual Meeting}, year={2019}, organization={AMS} }
Generating Adversarial Driving Scenarios in High-Fidelity Simulators
Abeysirigoonawardena; Yasasa; Florian Shkurti; Gregory Dudek.

20192019 International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
In recent years self-driving vehicles have become more commonplace on public roads, with the promise of bringing safety and efficiency to modern transportation systems. Increasing the reliability of these vehicles on the road requires an extensive suite of software tests, ideally performed on high-fidelity simulators, where multiple vehicles and pedestrians interact with the self-driving vehicle. It is therefore of critical importance to ensure that self-driving software is assessed against a wide range of challenging simulated driving
Topics
reinforcement learning
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@inproceedings{abeysirigoonawardena2019generating, title={Generating Adversarial Driving Scenarios in High-Fidelity Simulators}, author={Abeysirigoonawardena, Yasasa and Shkurti, Florian and Dudek, Gregory}, booktitle={2019 International Conference on Robotics and Automation (ICRA)}, pages={8271--8277}, year={2019}, organization={IEEE} }
Heterogeneous Robot Teams for Informative Sampling
Manderson; Travis; Sandeep Majanna; Gregory Dudek.

20192019 Workshop on Informative Path Planning and Adaptive Sampling at Robotics Science and Systems
Abstract
Abstract
In this paper we present a cooperative multi-robot strategy to adaptively explore and sample environments that are unfavorable for humans. We propose a methodology for a team of heterogeneous robots to collaborate on information based planning for applications like sampling thermal imagery in a wildfire affected site to assist with detecting spot fires and areas of residual fires, fire mapping and monitoring fire progression or applications in marine domain for coral reef monitoring and survey. We use Gabor filter based texture
Topics
localizationslamunderwater robotics
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@inproceedings{manderson2019heterogeneous, title={Heterogeneous Robot Teams for Informative Sampling}, author={Manderson, Travis and Majanna, Sandeep and Dudek, Gregory}, booktitle={2019 Workshop on Informative Path Planning and Adaptive Sampling at Robotics Science and Systems}, year={2019}, url={https://arxiv.org/abs/1906.07208} }
Heterogeneous Robot Teams for Informative Sampling
Manderson; Travis; Sandeep Majanna; Gregory Dudek

20192019 Workshop on Informative Path Planning and Adaptive Sampling at Robotics Science and Systems
Abstract
Abstract
In this paper we present a cooperative multi-robot strategy to adaptively explore and sample environments that are unfavorable for humans. We propose a methodology for a team of heterogeneous robots to collaborate on information based planning for applications like sampling thermal imagery in a wildfire affected site to assist with detecting spot fires and areas of residual fires, fire mapping and monitoring fire progression or applications in marine domain for coral reef monitoring and survey. We use Gabor filter based texture
Topics
localizationslamunderwater robotics
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@inproceedings{manderson2019heterogeneous, title={Heterogeneous Robot Teams for Informative Sampling}, author={Manderson, Travis and Majanna, Sandeep and Dudek, Gregory}, booktitle={2019 Workshop on Informative Path Planning and Adaptive Sampling at Robotics Science and Systems}, year={2019}, url={https://arxiv.org/abs/1906.07208} }
Investigating Trust Factors in Human-Robot Shared Control: Implicit Gender Bias Around Robot Voice
Wong; Alex; Anqi Xu; Gregory Dudek.

20192019 16th Conference on Computer and Robot Vision (CRV)
Abstract
Abstract
This paper explores the impact of warnings, audio feedback, and gender on human-robot trust in the context of autonomous driving and specifically shared robot control. We use pre-existing methods for the estimation and assessment of human-robot trust where trust was found to vary as a function of the quality of behavior of an autonomous driving controller. We extend these models and empirical methods to examine the impact of audio cues on trust, specifically studying the impacts of gender-specific audio cues on the elicitation of trust. Our
Topics
behavior cloninghuman-robot interactiontrust modeling
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@inproceedings{wong2019investigating, title={Investigating Trust Factors in Human-Robot Shared Control: Implicit Gender Bias Around Robot Voice}, author={Wong, Alex and Xu, Anqi and Dudek, Gregory}, booktitle={2019 16th Conference on Computer and Robot Vision (CRV)}, pages={195--200}, year={2019}, organization={IEEE} }
Mofi: Environment-Independent Device-Free Human Motion Detection via WiFi
X. Chen; H. Li; C. Zhou; S. Liu; G. Dudek

2019Proceedings of the RTSS@Work, pp. 1--2, 2019
Abstract
Abstract
Mofi: Environment-Independent Device-Free Human Motion Detection via WiFi
Topics
anomaly detectiontelecommunications
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@misc{mofienvironmentindependentdevicefreehuma, author = {X. Chen and H. Li and C. Zhou and S. Liu and G. Dudek}, title = {Mofi: Environment-Independent Device-Free Human Motion Detection via WiFi}, year = {2019}, journal = {Proceedings of the RTSS@Work, pp. 1--2, 2019}, }

Physics Guided ML: Emerging AI Opportunities for Weather and Climate

Kumar; Vipin; Valliappa Lakshmanan; Lucas Joppa; Gregory Dudek; Surya Karthik Mukkavilli; Amy McGovern.

201999th American Meteorological Society Annual Meeting

Abstract

99th American Meteorological Society Annual Meeting

Topics

bayesian inferencecomplexity boundsknowledge distillationmarkov chain monte carlomarkov random fieldstelecommunications

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@inproceedings{kumar2019physics,
  title={Physics Guided ML: Emerging AI Opportunities for Weather and Climate},
  author={Kumar, Vipin and Lakshmanan, Valliappa and Joppa, Lucas and Dudek, Gregory and Mukkavilli, Surya Karthik and McGovern, Amy},
  booktitle={99th American Meteorological Society Annual Meeting},
  year={2019},
  organization={AMS},
  note={Side panel: ``Side Panel Towards Planetary Intelligence: On the Synergistic Future of AI, Weather and Climate''}
}

Policy Search with Non-uniform State Representations for Environmental Sampling
Sandeep Manjanna; Herke van Hoof; Gregory Dudek

2019International Conference on Machine Learning, workshop on Climate Change, in association with NeurIPS 2019
Abstract
Abstract
Surveying fragile ecosystems like coral reefs is important to monitor the effects of climate change. We present an adaptive sampling technique that generates efficient trajectories covering hotspots in the region of interest at a high rate. A key feature of our sampling algorithm is the ability to generate action plans for any new hotspot distribution using the parameters learned on other similar looking distributions.
Topics
adaptive samplingcomplexity boundscoral reef mappinggraph theorylocalizationreinforcement learningslamunderwater robotics
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BibTeX
@inproceedings{manjanna2019policy, author = {Sandeep Manjanna and Herke van Hoof and Gregory Dudek}, title = {Policy Search with Non-uniform State Representations for Environmental Sampling}, booktitle = {International Conference on Machine Learning, workshop on Climate Change, in association with NeurIPS 2019}, year = {2019}, url = {https://s3.us-east-1.amazonaws.com/climate-change-ai/papers/icml2019/1/paper.pdf} }
Semantic Mapping for View-Invariant Relocalization
Li; Jimmy; David Meger; Gregory Dudek.

20192019 International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We propose a system for visual simultaneous localization and mapping (SLAM) that combines traditional local appearance-based features with semantically meaningful object landmarks to achieve both accurate local tracking and highly view-invariant object-driven relocalization. Our mapping process uses a sampling-based approach to efficiently infer the 3D pose of object landmarks from 2D bounding box object detections. These 3D landmarks then serve as a view-invariant representation which we leverage to achieve camera
Topics
3d reconstructionlandmark-based methodslocalizationobject recognitionreinforcement learningslam
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@inproceedings{li2019semantic, title={Semantic Mapping for View-Invariant Relocalization}, author={Li, Jimmy and Meger, David and Dudek, Gregory}, booktitle={2019 International Conference on Robotics and Automation (ICRA)}, pages={7108--7115}, year={2019}, organization={IEEE} }
Underwater Communication Using Full-Body Gestures and Optimal Variable-Length Prefix Codes
Koreitem; Karim; Li; Jimmy; Karp; Ian; Manderson; Travis; Dudek; Gregory.

2019Proceedings of the 2019 IEEE International Conference on Robotics and Automation
Abstract
Abstract
In this paper we consider inter-robot communication in the context of joint activities. In particular, we focus on convoying and passive communication for radio-denied environments by using whole-body gestures to provide cues regarding future actions. We develop a communication protocol whereby information described by codewords is transmitted by a series of actions executed by a swimming robot. These action sequences are chosen to optimize robustness and transmission duration given the observability, natural
Topics
complexity boundscooperative localizationgesture-based interactiongraph theorylocalizationobject recognitionrobotic collectivesslamtelecommunicationsunderwater navigationunderwater robotics
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@inproceedings{koreitem2019underwater, author = {Karim Koreitem and Jimmy Li and Ian Karp and Travis Manderson and Gregory Dudek}, title = {Underwater Communication Using Full-Body Gestures and Optimal Variable-Length Prefix Codes}, booktitle = {Proceedings of the 2019 IEEE International Conference on Robotics and Automation}, year = {2019} }
Adaptive exploration and sampling by heterogeneous robotic team
Sandeep Manjanna; Alberto Quattrini Li; Ryan N. Smith; Ioannis Rekleitis; Gregory Dudek

2018Proc. of the IEEE International Conference on Robotics and Automation (ICRA 2018)
Abstract
Abstract
Physical sampling of water for off-site analysis is necessary for many applications like monitoring the quality of drinking water in reservoirs, understanding marine ecosystems, and measuring contamination levels in fresh-water systems. Robotic sampling enables to strategically collect water samples based on real-time measurements of physical and chemical properties gathered with onboard sensors. In this paper, we present a multi-robot, data-driven, watersampling strategy, where autonomous surface vehicles plan and execute
Topics
adaptive samplingexploration strategiesunderwater robotics
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@inproceedings{Manjanna2018, author = {Sandeep Manjanna and Alberto Quattrini Li and Ryan N. Smith and Ioannis Rekleitis and Gregory Dudek}, title = {Adaptive exploration and sampling by heterogeneous robotic team}, booktitle = {Proc. of the IEEE International Conference on Robotics and Automation (ICRA 2018)}, year = {2018}, address = {Sydney, Australia} }
Autonomous Marine Sampling Enhanced by Strategically Deployed Drifters in Marine Flow Fields
Hansen; J.; Manjanna; S.; Li; A. Q.; Rekleitis; I.; Dudek; G.

2018OCEANS 2018 MTS/IEEE Charleston
Abstract
Abstract
We present a transportable system for ocean observations in which a small autonomous surface vehicle (ASV) adaptively collects spatially diverse samples with aid from a team of inexpensive, passive floating sensors known as drifters. Drifters can provide an increase in spatial coverage at little cost as they are propelled about the survey area by the ambient flow field instead of with actuators. Our iterative planning approach demonstrates how we can use the ASV to strategically deploy drifters into points of the flow field for high expected
Topics
adaptive samplinglocalizationslamunderwater robotics
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@inproceedings{hansen2018autonomous, title={Autonomous Marine Sampling Enhanced by Strategically Deployed Drifters in Marine Flow Fields}, author={Hansen, J. and Manjanna, S. and Li, A. Q. and Rekleitis, I. and Dudek, G.}, booktitle={OCEANS 2018 MTS/IEEE Charleston}, pages={1--7}, year={2018} }
Coverage optimization with non-actuated, floating mobile sensors using iterative trajectory planning in marine flow fields
Hansen; J.; Dudek; G.

20182018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
This paper considers a spatial coverage problem in which a network of passive floating sensors is used to collect samples in a body of water. We employ an iterative measurement and modeling scheme to incrementally deploy sensors so as to achieve spatial coverage, despite only controlling the initial sample point. Once deployed, sensors are moved about a survey area by ambient surface currents. We demonstrate our results in simulation on 40 different ocean flow fields and compare against several baselines. This work provides a
Topics
underwater robotics
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@inproceedings{hansen2018coverage, title={Coverage optimization with non-actuated, floating mobile sensors using iterative trajectory planning in marine flow fields}, author={Hansen, J. and Dudek, G.}, booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={1906--1912}, year={2018}, organization={IEEE} }
Coverage optimization with non-actuated, floating mobile sensors using iterative trajectory planning in marine flow fields
Hansen; J.; Dudek; G.

20182018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
This paper considers a spatial coverage problem in which a network of passive floating sensors is used to collect samples in a body of water. We employ an iterative measurement and modeling scheme to incrementally deploy sensors so as to achieve spatial coverage, despite only controlling the initial sample point. Once deployed, sensors are moved about a survey area by ambient surface currents. We demonstrate our results in simulation on 40 different ocean flow fields and compare against several baselines. This work provides a
Topics
underwater robotics
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@inproceedings{hansen2018coverage, title={Coverage optimization with non-actuated, floating mobile sensors using iterative trajectory planning in marine flow fields}, author={Hansen, J. and Dudek, G.}, booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={1906--1912}, year={2018}, organization={IEEE} }
Gaze Selection for Enhanced Visual Odometry During Navigation
Manderson, Travis; Holliday, Andrew; Dudek, Gregory

2018Proceedings of the Conference on Computer and Robot Vision (CRV 2018)
Abstract
Abstract
We present an approach to enhancing visual odometry and Simultaneous Localization and Mapping (SLAM) in the context of robot navigation by actively modulating the gaze direction to enhance the quality of the odometric estimates that are returned. We focus on two quality factors: i) stability of the visual features, and ii) consistency of the visual features with respect to robot motion and the associated correspondence between frames. We assume that local texture measures are associated with underlying scene content and thus with the quality of
Topics
localization
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@inproceedings{manderson2018gaze, title={Gaze Selection for Enhanced Visual Odometry During Navigation}, author={Manderson, Travis and Holliday, Andrew and Dudek, Gregory}, booktitle={Proceedings of the Conference on Computer and Robot Vision (CRV 2018)}, pages={110--117}, year={2018}, organization={IEEE}, address={Toronto, Canada} }
GPU-Assisted Learning on an Autonomous Marine Robot for Vision-Based Navigation and Image Understanding
Travis Manderson; Gregory Dudek

2018Proceedings of Oceans Conference and Exposition 2018
Abstract
Abstract
We present a GPU-based integrated robotic platform that enables collision avoidance, navigation, and image understanding on a single underwater vehicle. The platform enables observational tasks such as coral reef health assessment by enabling simultaneous operation of multiple image analysis taskswhile navigating in close proximity to obstacles. The integration of a GPU allows us to leverage deep neural networks for collision avoidance and automated object detection and classification while a general purpose CPU processes
Topics
coral reef mappingdeep learninggenerative ailocalizationmarine biologyslamunderwater robotics
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@inproceedings{manderson2018gpu, author = {Travis Manderson and Gregory Dudek}, title = {GPU-Assisted Learning on an Autonomous Marine Robot for Vision-Based Navigation and Image Understanding}, booktitle = {Proceedings of Oceans Conference and Exposition 2018}, year = {2018}, address = {Charleston, United States} }
Heterogeneous Multi-Robot System for Exploration and Strategic Water Sampling
Manjanna; S.; Li; A. Q.; Smith; R. N.; Rekleitis; I.; Dudek; G. (2018; May).

20182018 IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Physical sampling of water for off-site analysis is necessary for many applications like monitoring the quality of drinking water in reservoirs, understanding marine ecosystems, and measuring contamination levels in fresh-water systems. In this paper, the focus is on algorithms for efficient measurement and sampling using a multi-robot, data-driven, water-sampling behavior, where autonomous surface vehicles plan and execute water sampling using the chlorophyll density as a cue for plankton-rich water samples. We use two
Topics
localizationmarine biologyslamunderwater robotics
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@inproceedings{Manjanna2018, author = {Manjanna, S. and Li, A. Q. and Smith, R. N. and Rekleitis, I. and Dudek, G.}, title = {Heterogeneous Multi-Robot System for Exploration and Strategic Water Sampling}, booktitle = {2018 IEEE International Conference on Robotics and Automation (ICRA)}, year = {2018}, month = {May}, pages = {1--8} }
Model-Based Probabilistic Pursuit via Inverse Reinforcement Learning
Florian Shkurti; Nikhil Kakodkar; Gregory Dudek

2018Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2018)
Abstract
Abstract
We address the integrated prediction, planning, and control problem that enables a single follower robot (the photographer) to quickly re-establish visual contact with a moving target (the subject) that has escaped the follower's field of view. We deal with this scenario, which reactive controllers are typically ill-equipped to handle, by making plausible predictions about the long-and short-term behavior of the target, and planning pursuit paths that will maximize the chance of seeing the target again. At the core of our pursuit method is the use
Topics
bayesian inferencecomplexity boundshuman-robot interactioninverse reinforcement learninglocalizationmarkov chain monte carlomarkov random fieldsobject recognitionpath planningslamunderwater robotics
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@inproceedings{Shkurti2018, author = {Florian Shkurti and Nikhil Kakodkar and Gregory Dudek}, title = {Model-Based Probabilistic Pursuit via Inverse Reinforcement Learning}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2018)}, year = {2018}, address = {Sydney, Australia}, month = {May} }
Navigation in the Service of Enhanced Pose Estimation
Manderson, Travis; Cheng, Ran; Meger, David; Dudek, Gregory

2018Proceedings of the 2018 International Symposium on Experimental Robotics (ISER 2018)
Abstract
Abstract
This paper addresses robust vision-based odometry for underwater robotics by autonomously adjusting the robot trajectory in real-time to optimize the quality of ongoing visual feedback. It is well-known that accurate Visual Odometry (VO) depends on both the presence of sufficient smooth surfaces with manageable reflectance functions and The robotic vehicle used in this work is a fully-autonomous marine system that uses vision for collision avoidance, navigation, and image understanding on a single vehicle (Fig. 2). This vehicle is a variant of
Topics
localizationunderwater navigationunderwater robotics
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@inproceedings{manderson2018navigation, title={Navigation in the Service of Enhanced Pose Estimation}, author={Manderson, Travis and Cheng, Ran and Meger, David and Dudek, Gregory}, booktitle={Proceedings of the 2018 International Symposium on Experimental Robotics (ISER 2018)}, year={2018}, address={Buenos Aires, Argentina} }
Planning in Dynamic Environments with Conditional Autoregressive Models
Hansen; Johanna; Kyle Kastner; Aaron Courville; Gregory Dudek.

2018arXiv preprint arXiv:1811.10097
Abstract
Abstract
We demonstrate the use of conditional autoregressive generative models (van den Oord et al., 2016a) over a discrete latent space (van den Oord et al., 2017b) for forward planning with MCTS. In order to test this method, we introduce a new environment featuring varying difficulty levels, along with moving goals and obstacles. The combination of high-quality frame generation and classical planning approaches nearly matches true environment performance for our task, demonstrating the usefulness of this method for model-based
Topics
generative aireinforcement learning
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@article{hansen2018planning, title={Planning in Dynamic Environments with Conditional Autoregressive Models}, author={Hansen, Johanna and Kastner, Kyle and Courville, Aaron and Dudek, Gregory}, journal={arXiv preprint arXiv:1811.10097}, year={2018} }
Reinforcement Learning with Non-uniform State Representations for Adaptive Search
Manjanna; S.; van Hoof; H.; Dudek; G. (2018; August).

20182018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Abstract
Abstract
R(τ) = exp(−T/c) with T is the time until the target is found if the target is found within H time steps, or 0 otherwise4. 3The reward map q is not normalized, yet after clearing a fraction g or probability mass, the probability that the target has not been found yet is 1 − g. If the target were not found yet, the normalized probability that the target Dudek, “Data-driven selective sampling for marine vehicles using multi-scale paths,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, September
Topics
exploration strategieslocalizationpath planningreinforcement learningslam
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@inproceedings{Manjanna2018, author = {Manjanna, S. and van Hoof, H. and Dudek, G.}, title = {Reinforcement Learning with Non-uniform State Representations for Adaptive Search}, booktitle = {2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)}, year = {2018}, month = {August}, pages = {1--7} }
Scale-Robust Localization Using General Object Landmarks
Holliday; A.; Dudek; G.

20182018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Visual localization under large changes in scale is an important capability in many robotic mapping applications, such as localizing at low altitudes in maps built at high altitudes, or performing loop closure over long distances. Existing approaches, however, are robust only up to about a 3× difference in scale between map and query images. We propose a novel combination of deep-learning-based object features and state-of-the-art SIFT point-features that yields improved robustness to scale change. This technique is training-free and class
Topics
coral reef mappingenvironment mappinglandmark-based methodslocalizationslamunderwater robotics
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@inproceedings{holliday2018scale, title={Scale-Robust Localization Using General Object Landmarks}, author={Holliday, A. and Dudek, G.}, booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={1688--1694}, year={2018}, organization={IEEE} }
Semantic Scene Models for Visual Localization Under Large Viewpoint Changes
Jimmy Li; Zhaoqi Xu; David Meger; Gregory Dudek

2018Proceedings of the 15th Conference on Computer and Robot Vision (CRV 2018)
Abstract
Abstract
We propose an approach for camera pose estimation under large viewpoint changes using only 2D RGB images. This enables a mobile robot to relocalize itself with respect to a previously-visited scene when seeing it again from a completely new vantage point. In order to overcome large appearance changes, we integrate a variety of cues, including object detections, vanishing points, structure from motion, and object-to-object context in order to constrain the camera geometry, while simultaneously estimating the 3D pose of covisible
Topics
localizationslam
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@inproceedings{Li2018, author = {Jimmy Li and Zhaoqi Xu and David Meger and Gregory Dudek}, title = {Semantic Scene Models for Visual Localization Under Large Viewpoint Changes}, booktitle = {Proceedings of the 15th Conference on Computer and Robot Vision (CRV 2018)}, year = {2018}, address = {Toronto}, month = {May} }
Synthesizing Neural Network Controllers with Probabilistic Model-Based Reinforcement Learning
Higuera; J. C. G.; Meger; D.; Dudek; G. (2018; October).

20182018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We present an algorithm for rapidly learning neural network policies for robotics systems. The algorithm follows the model-based reinforcement learning paradigm and improves upon existing algorithms: PILeO and a sample-based version of PILeo with neural network dynamics (Deep-PILeO). To improve convergence, we propose a model-based algorithm that uses fixed random numbers and clips gradients during optimization. We propose training a neural network dynamics model using variational dropout with truncated Log
Topics
localizationreinforcement learningunderwater roboticsvariational methods
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@inproceedings{higuera2018synthesizing, title={Synthesizing Neural Network Controllers with Probabilistic Model-Based Reinforcement Learning}, author={Higuera, Juan Camilo Gamboa and Meger, David and Dudek, Gregory}, booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={2538--2544}, year={2018}, organization={IEEE} }
Synthetically trained 3d visual tracker of underwater vehicles
Koreitem; K.; Li; J.; Karp; I.; Manderson; T.; Shkurti; F.; Dudek; G. (2018; October).

2018OCEANS 2018 MTS/IEEE Charleston
Abstract
Abstract
We present a method for visually detecting and tracking the 3D pose of autonomous underwater vehicles, which aims to enable robust multi-robot convoying. We follow the approach of tracking-by-detection, which combines the robust, drift-free nature of object detection with the temporal consistency of tracking algorithms. Central to our method is a multi-output convolutional network that jointly predicts whether the target robot is present in the image (classification), the 2D bounding box around the target in the image plane, and
Topics
robotic collectivesunderwater robotics
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@inproceedings{koreitem2018synthetically, title={Synthetically trained 3d visual tracker of underwater vehicles}, author={Koreitem, K. and Li, J. and Karp, I. and Manderson, T. and Shkurti, F. and Dudek, G.}, booktitle={OCEANS 2018 MTS/IEEE Charleston}, pages={1--7}, year={2018}, organization={IEEE} }
Vision-based Autonomous Underwater Swimming in Dense Coral for Combined Collision Avoidance and Target Selection
Manderson, Travis; Gamboa Higuera, Juan Camilo; Cheng, Ran; Dudek, Gregory

20182018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We address the problem of learning vision-based, collision-avoiding, and target-selecting controllers in 3D, specifically in underwater environments densely populated with coral reefs. Using a highly maneuverable, dynamic, six-legged (or flippered) vehicle to swim underwater, we exploit real time visual feedback to make close-range navigation decisions that would be hard to achieve with other sensors. Our approach uses computer vision as the sole mechanism for both collision avoidance and visual target selection. In particular, we
Topics
complexity boundscoral reef mappingexploration strategiesgraph theorylocalizationmarine biologyslamunderwater robotics
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@inproceedings{manderson2018vision, title={Vision-based Autonomous Underwater Swimming in Dense Coral for Combined Collision Avoidance and Target Selection}, author={Manderson, Travis and Gamboa Higuera, Juan Camilo and Cheng, Ran and Dudek, Gregory}, booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={2018--2025}, year={2018}, organization={IEEE} }
Visual identification of biological motion for underwater human–robot interaction
J Sattar; G Dudek

2018Autonomous Robots
Abstract
Abstract
We present an algorithm for underwater robots to visually detect and track human motion. Our objective is to enable human–robot interaction by allowing a robot to follow behind a human moving in (up to) six degrees of freedom. In particular, we have developed a system to allow a robot to detect, track and follow a scuba diver by using frequency-domain detection of biological motion patterns. The motion of biological entities is characterized by combinations of periodic motions which are inherently distinctive. This is especially true of
Topics
localizationunderwater robotics
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@misc{visualidentificationofbiologicalmotionfo, author = {J Sattar and G Dudek}, title = {Visual identification of biological motion for underwater human–robot interaction}, year = {2018}, journal = {Autonomous Robots}, url = {https://link.springer.com/article/10.1007/s10514-017-9644-y}, }
Adapting learned robotics behaviours through policy adjustment
J. C. G. Higuera; D. Meger; G. Dudek

2017IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We present an approach to learning control policies for physical robots that achieves high efficiency by adjusting existing policies that have been learned on similar source systems, such as a similar robot with different physical parameters, or an approximate dynamics model simulator. This can be viewed as calibrating a policy learned on a source system, to match a desired behaviour in similar target systems. Our approach assumes that the trajectories described by the source robot are feasible on the target robot. By making this
Topics
adaptive controlreinforcement learning
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@inproceedings{Higuera2017, author = {J. C. G. Higuera and D. Meger and G. Dudek}, title = {Adapting learned robotics behaviours through policy adjustment}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2017}, pages = {5837--5843} }
Benchmark environments for multitask learning in continuous domains
P. Henderson; W.-D. Chang; F. Shkurti; J. Hansen; D. Meger; G. Dudek

2017IROS
Abstract
Abstract
As demand drives systems to generalize to various domains and problems, the study of multitask, transfer and lifelong learning has become an increasingly important pursuit. In discrete domains, performance on the Atari game suite has emerged as the de facto benchmark for assessing multitask learning. However, in continuous domains there is a lack of agreement on standard multitask evaluation environments which makes it difficult to compare different approaches fairly. In this work, we describe a benchmark set of tasks that
Topics
reinforcement learning
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@article{Henderson2017, author = {P. Henderson and W.-D. Chang and F. Shkurti and J. Hansen and D. Meger and G. Dudek}, title = {Benchmark environments for multitask learning in continuous domains}, year = {2017}, journal = {IROS}, }
Context-coherent scenes of objects for camera pose estimation
Li, J.; Meger, D.; Dudek, G.

20172017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We propose an approach to vision-based pose estimation using object recognition and identity. Whereas feature based scene recognition and pose estimation methods are well established as effective means for estimating motion and recognizing locations, feature-based methods depend critically on the detection of common local features from one view of a scene to another. We focus on place recognition and pose change estimation in the context of large changes in viewing position, even to the extent that no common surfaces are
Topics
localizationobject recognitionplace recognition
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@inproceedings{li2017context, title={Context-coherent scenes of objects for camera pose estimation}, author={Li, J. and Meger, D. and Dudek, G.}, booktitle={2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={}, year={2017}, month={September}, organization={IEEE} }
Control, localization and human interaction with an autonomous lighter-than-air performer
D St-Onge; PY Brèches; I Sharf; N Reeves; I. Rekleitis; P. Abouzakhm; Y. Girdhar; A. Harmat; G. Dudek; P. Giguere

2017Robotics and …
Abstract
Abstract
Due to the recent technological progress, Human–RobotInteraction (HRI) has become a major field of research in both engineering and artistic realms, particularly so in the last decade. The mainstream interests are, however, extremely diverse: challenges are continuously shifting, the evolution of robot'skills, as well as the advances in methods for understanding their environment radically impact the design and implementation of research prototypes. When directly deployed in a public installation or artistic performances, robots
Topics
aerial roboticsenvironment mappinghuman-robot interactionlocalization
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@misc{controllocalizationandhumaninteractionwi, author = {D St-Onge and PY Brèches and I Sharf and N Reeves and I. Rekleitis and P. Abouzakhm and Y. Girdhar and A. Harmat and G. Dudek and P. Giguere}, title = {Control, localization and human interaction with an autonomous lighter-than-air performer}, year = {2017}, journal = {Robotics and …}, url = {https://www.sciencedirect.com/science/article/pii/S0921889016306674}, }
Data-driven selective sampling for marine vehicles using multi-scale paths
S. Manjanna; G. Dudek

20172017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
This paper addresses adaptive coverage of a spatial field without prior knowledge. Our application in this paper is to cover a region of the sea surface using a robotic boat, although the algorithmic approach has wider applicability. We propose an anytime planning technique for efficient data gathering using point-sampling based on non-uniform data-driven coverage. Our goal is to sense a particular region of interest in the environment and be able to reconstruct the measured spatial field. Since there are autonomous agents
Topics
adaptive samplingcomplexity boundslocalizationpath planningrobotic collectivesslamunderwater robotics
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@inproceedings{manjanna2017data, author = {S. Manjanna and G. Dudek}, title = {Data-driven selective sampling for marine vehicles using multi-scale paths}, booktitle = {2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2017}, month = {September} }
From simulation to the field: Learning to swim with the aqua robot
J. C. G. Higuera; D. Meger; G. Dudek

2017ROSCon 2017
Abstract
Abstract
From simulation to the field: Learning to swim with the aqua robot
Topics
underwater robotics
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@inproceedings{Higuera2017, author = {J. C. G. Higuera and D. Meger and G. Dudek}, title = {From simulation to the field: Learning to swim with the aqua robot}, booktitle = {ROSCon 2017}, year = {2017}, month = sep }
Learning Seasonal Phytoplankton Communities with Topic Models
Kalmbach, A.; Sosik, Heidi M.; Dudek, Gregory; Girdhar, Yogesh

2017IEEE OceansAward winner
Abstract
Abstract
In this work we develop and demonstrate a probabilistic generative model for phytoplankton communities. The proposed model takes counts of a set of phytoplankton taxa in a timeseries as its training data, and models communities by learning sparse co-occurrence structure between the taxa. Our model is probabilistic, where communities are represented by probability distributions over the species, and each time-step is represented by a probability distribution over the communities. The proposed approach uses a non
Topics
marine biologyunderwater robotics
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@inproceedings{kalmbach2017learning, title={Learning Seasonal Phytoplankton Communities with Topic Models}, author={Kalmbach, A. and Sosik, Heidi M. and Dudek, Gregory and Girdhar, Yogesh}, booktitle={IEEE Oceans}, year={2017}, note={Award winner}, eprint={1711.09013}, archivePrefix={arXiv}, primaryClass={cs.LG} }
Phytoplankton hotspot prediction with an unsupervised spatial community model
Kalmbach, A.; Girdhar, Yogesh; Sosik, Heidi M.; Dudek, Gregory

2017IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Many interesting natural phenomena are sparsely distributed and discrete. Locating the hotspots of such sparsely distributed phenomena is often difficult because their density gradient is likely to be very noisy. We present a novel approach to this search problem, where we model the co-occurrence relations between a robot's observations with a Bayesian nonparametric topic model. This approach makes it possible to produce a robust estimate of the spatial distribution of the target, even in the absence of direct target
Topics
localizationmarine biologyslamunderwater robotics
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@inproceedings{kalmbach2017phytoplankton, title={Phytoplankton hotspot prediction with an unsupervised spatial community model}, author={Kalmbach, A. and Girdhar, Yogesh and Sosik, Heidi M. and Dudek, Gregory}, booktitle={IEEE International Conference on Robotics and Automation (ICRA)}, year={2017}, pages={2017}, note={arXiv preprint arXiv:1703.07309} }
Robotic coral reef health assessment using automated image analysis
Manderson; Travis; Jimmy Li; Natasha Dudek; David Meger; Gregory Dudek.

2017Journal of Field …
Abstract
Abstract
This paper presents a system capable of autonomous surveillance and analysis of coral reef ecosystems using natural lighting. We describe our strategy to safely and effectively deploy a small marine robot to inspect a reef using its digital cameras. Image analysis using a (RBF‐SVM) radial basis function‐support vector machines in combination with (LBP) local binary pattern, Gabor and Hue descriptors developed in this work are able to analyze the resulting image data automatically and reliably by learning from the annotations of expert marine
Topics
complexity boundscoral reef mappinggraph theorymarine biologyobject recognitionunderwater navigationunderwater robotics
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@misc{roboticcoralreefhealthassessmentusingaut, author = {Manderson and Travis and Jimmy Li and Natasha Dudek and David Meger and Gregory Dudek.}, title = {Robotic coral reef health assessment using automated image analysis}, year = {2017}, journal = {Journal of Field …}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.21698}, }
Topologically distinct trajectory predictions for probabilistic pursuit
F. Shkurti; G. Dudek

20172017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We address the integrated planning and control problem that enables a single follower robot (the “photographer”) to maintain a moving target (the “subject”) in its field of view for as long as possible. We propose a real-time pursuit algorithm that seamlessly handles the often neglected, yet unavoidable, scenario in which the target escapes the follower's field of view; a scenario that simple, reactive controllers are ill-equipped to handle. Our algorithm aims to minimize the expected time until visual contact is re-established, which enables the
Topics
complexity boundsgraph theoryhuman-robot interactionlocalizationreinforcement learningslam
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@inproceedings{shkurti2017topologically, author = {F. Shkurti and G. Dudek}, title = {Topologically distinct trajectory predictions for probabilistic pursuit}, booktitle = {2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, month = {September}, year = {2017} }
Underwater multi-robot convoying using visual tracking by detection
F. Shkurti; W.-D. Chang; P. Henderson; M. J. Islam; J. C. G. Higuera; J. Li; T. Manderson; A. Xu; G. Dudek; J. Sattar

20172017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments. Our method is based on the idea of tracking-by-detection, which interleaves efficient model-based object detection with temporal filtering of image-based bounding box estimation. This approach has the important advantage of mitigating tracking drift (ie drifting away from the target object), which is a common symptom of model-free trackers and is detrimental to sustained
Topics
robotic collectivesunderwater navigationunderwater robotics
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@inproceedings{Shkurti2017, author = {F. Shkurti and W.-D. Chang and P. Henderson and M. J. Islam and J. C. G. Higuera and J. Li and T. Manderson and A. Xu and G. Dudek and J. Sattar}, title = {Underwater multi-robot convoying using visual tracking by detection}, booktitle = {2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2017}, month = {September}, doi = {10.1109/IROS.2017.8202133}, note = {Also available as arXiv preprint arXiv:1709.08292} }
Data correlation and comparison from multiple sensors over a coral reef with a team of heterogeneous aquatic robots
Quattrini Li; A; I. Rekleitis; S. Manjanna; N. Kakodkar; J. Hansen; G. Dudek; L. Bobadilla; J. Anderson; R. Smith

2016International Symposium of Experimental Robotics (ISER)
Abstract
Abstract
This paper presents experimental insights from the deployment of an ensemble of heterogeneous autonomous sensor systems over a shallow coral reef. Visual, inertial, GPS, and ultrasonic data collected are compared and correlated to produce a comprehensive view of the health of the coral reef. Coverage strategies are discussed with a focus on the use of informed decisions to maximize the information collected during a fixed period of time.
Topics
coral reef mappinglocalizationslamunderwater robotics
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@inproceedings{quattrini2016data, title={Data correlation and comparison from multiple sensors over a coral reef with a team of heterogeneous aquatic robots}, author={Quattrini Li, Adriano and Rekleitis, Ioannis and Manjanna, Santhosh and Kakodkar, Nikhil and Hansen, John and Dudek, Gregory and Bobadilla, Leonardo and Anderson, John and Smith, Ryan}, booktitle={International Symposium of Experimental Robotics (ISER)}, year={2016} }
Efficient terrain driven coral coverage using gaussian processes for mosaic synthesis
Manjanna; S.; N. Kakodkar; M. Meghjani; G. Dudek

20162016 13th Conference on Computer and Robot Vision (CRV)
Abstract
Abstract
In this paper we present an efficient method for visual mapping of open water environments using exploration and reward identification followed by selective visual coverage. In particular, we consider the problem of visual mapping a shallow water coral reef to provide an environmental assay. Our approach has two stages based on two classes of sensors: bathymetric mapping and visual mapping. We use a robotic boat to collect bathymetric data using a sonar sensor for the first stage and video data using a visual sensor for the second
Topics
coral reef mappingexploration strategieslocalizationslamunderwater robotics
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@inproceedings{Manjanna2016, author = {S. Manjanna and N. Kakodkar and M. Meghjani and G. Dudek}, title = {Efficient terrain driven coral coverage using gaussian processes for mosaic synthesis}, booktitle = {2016 13th Conference on Computer and Robot Vision (CRV)}, year = {2016}, pages = {448--455}, publisher = {IEEE} }

Fast and efficient rendezvous in street networks

Meghjani; M; G. Dudek

20162016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Abstract

Fast and efficient rendezvous in street networks

Topics

complexity bounds

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@inproceedings{Meghjani2016,
  author    = {Meghjani, Maithilee and Dudek, Gregory},
  title     = {Fast and efficient rendezvous in street networks},
  booktitle = {2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year      = {2016},
  pages     = {1887--1893},
  publisher = {IEEE}
}

Learning to generalize 3d spatial relationships
Li; Jimmy; D. Meger; G. Dudek

2016Robotics and Automation (ICRA), 2016 IEEE International Conference on
Abstract
Abstract
This paper presents an approach to learn meaningful spatial relationships in an unsupervised fashion from the distribution of 3D object poses in the real world. Our approach begins by extracting an over-complete set of features to describe the relative geometry of two objects. Each relationship type is modeled using a relevance-weighted distance over this feature space. This effectively ignores irrelevant feature dimensions. Our algorithm RANSEM for determining subsets of data that share a relationship as well as the
Topics
bayesian inferencecomplexity boundsdeep learningdomain adaptationenvironment mappingexploration strategiesgraph theoryinverse reinforcement learningknowledge distillationlandmark-based methodslocalizationmarkov chain monte carlomarkov random fieldsobject recognitionpath planningplace recognitionrendezvousrobotic collectivesslamtelecommunicationsvariational methods
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@inproceedings{li2016learning, title={Learning to generalize 3d spatial relationships}, author={Li, Jimmy and Meger, D. and Dudek, G.}, booktitle={Robotics and Automation (ICRA), 2016 IEEE International Conference on}, pages={5744--5749}, year={2016}, organization={IEEE} }
Maintaining efficient collaboration with trust-seeking robots
Xu; A; G. Dudek

2016Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on
Abstract
Abstract
In this work, we grant robot agents the capacity to sense and react to their human supervisor's changing trust state, as a means to maintain the efficiency of their collaboration. We propose the novel formulation of Trust-Aware Conservative Control (TACtiC), in which the agent alters its behaviors momentarily whenever the human loses trust. This trust-seeking robot framework builds upon an online trust inference engine and also incorporates an interactive behavior adaptation technique. We present end-to-end instantiations of trust
Topics
adaptive controlaerial roboticsbehavior cloninghuman-robot interactiontrust modeling
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@inproceedings{xu2016maintaining, title={Maintaining efficient collaboration with trust-seeking robots}, author={Xu, A. and Dudek, G.}, booktitle={Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on}, pages={3312--3319}, year={2016}, organization={IEEE} }
Maintaining efficient collaboration with trust-seeking robots
Xu; A; G. Dudek

2016Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on
Abstract
Abstract
In this work, we grant robot agents the capacity to sense and react to their human supervisor's changing trust state, as a means to maintain the efficiency of their collaboration. We propose the novel formulation of Trust-Aware Conservative Control (TACtiC), in which the agent alters its behaviors momentarily whenever the human loses trust. This trust-seeking robot framework builds upon an online trust inference engine and also incorporates an interactive behavior adaptation technique. We present end-to-end instantiations of trust
Topics
adaptive controlaerial roboticsbehavior cloninghuman-robot interactiontrust modeling
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@inproceedings{xu2016maintaining, title={Maintaining efficient collaboration with trust-seeking robots}, author={Xu, A. and Dudek, G.}, booktitle={Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on}, pages={3312--3319}, year={2016}, organization={IEEE} }

Modeling curiosity in a mobile robot for long-term autonomous exploration and monitoring

Girdhar; Yogesh; Gregory Dudek

2016Autonomous Robots

Abstract

This paper presents a novel approach to modeling curiosity in a mobile robot, which is useful for monitoring and adaptive data collection tasks, especially in the context of long term autonomous missions where pre-programmed missions are likely to have limited utility. We use a realtime topic modeling technique to build a semantic perception model of the environment, using which, we plan a path through the locations in the world with high semantic information content. The life-long learning behavior of the proposed perception

Topics

environment mappingpath planningslamvideo summaries

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@article{girdhar2016modeling,
 abstract = {This paper presents a novel approach to modeling curiosity in a mobile robot, which is useful for monitoring and adaptive data collection tasks, especially in the context of long term autonomous missions where pre-programmed missions are likely to have limited utility. We use a realtime topic modeling technique to build a semantic perception model of the environment, using which, we plan a path through the locations in the world with high semantic information content. The life-long learning behavior of the proposed perception},
 author = {Girdhar, Yogesh and Dudek, Gregory},
 journal = {Autonomous Robots},
 pages = {1267--1278},
 pub_year = {2016},
 publisher = {Springer},
 title = {Modeling curiosity in a mobile robot for long-term autonomous exploration and monitoring},
 venue = {Autonomous Robots},
 volume = {40}
}

Multi-target rendezvous search
Meghjani; M; G. Dudek

2016Proc. International Conference on Intelligent Robots and Systems (IROS)Nominee for best-paper award in the Search and Rescue category
Abstract
Abstract
In this paper, we examine multi-target search, where one or more targets must be found by a moving robot. Given the target's initial probability distribution or the expected search region, we present an analysis of three search strategies-Global maxima search, Local maxima search, and Spiral search. We aim at minimizing the mean-time-to-find and maximizing the total probability of finding the target. This leads to two types of illustrative performance metrics: minimum time capture and guaranteed capture. We validate the search strategies
Topics
exploration strategieslocalizationrendezvousslam
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@inproceedings{Meghjani2016, author = {Meghjani, Maithilee and Dudek, Gregory}, title = {Multi-target rendezvous search}, booktitle = {Proc. International Conference on Intelligent Robots and Systems (IROS)}, year = {2016}, pages = {2596--2603}, publisher = {IEEE}, note = {Nominee for best-paper award in the Search and Rescue category} }
Multi-target rendezvous search
Meghjani; M; G. Dudek

2016Proc. International Conference on Intelligent Robots and Systems (IROS)Nominee for best-paper award in the Search and Rescue category
Abstract
Abstract
In this paper, we examine multi-target search, where one or more targets must be found by a moving robot. Given the target's initial probability distribution or the expected search region, we present an analysis of three search strategies-Global maxima search, Local maxima search, and Spiral search. We aim at minimizing the mean-time-to-find and maximizing the total probability of finding the target. This leads to two types of illustrative performance metrics: minimum time capture and guaranteed capture. We validate the search strategies
Topics
exploration strategieslocalizationrendezvousslam
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@inproceedings{Meghjani2016, author = {Meghjani, Maithilee and Dudek, Gregory}, title = {Multi-target rendezvous search}, booktitle = {Proc. International Conference on Intelligent Robots and Systems (IROS)}, year = {2016}, pages = {2596--2603}, publisher = {IEEE}, note = {Nominee for best-paper award in the Search and Rescue category} }
Multi-target search strategies
Meghjani; M; S. Manjanna; G. Dudek

2016Proc. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)Finalist for best paper award
Abstract
Abstract
This paper addresses the problem of searching multiple non-adversarial targets using a mobile searcher in an obstacle-free environment. In practice, we are particularly interested in marine applications where the targets drift on the ocean surface. These targets can be surface sensors used for marine environmental monitoring, drifting debris, or lost divers in open water. Searching for a floating target requires prior knowledge about the search region and an estimate of the target's motion. This task becomes challenging when searching for
Topics
exploration strategieslocalizationrendezvousslamunderwater robotics
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@inproceedings{Meghjani2016, author = {Meghjani, M. and Manjanna, S. and Dudek, G.}, title = {Multi-target search strategies}, booktitle = {Proc. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)}, year = {2016}, pages = {328--333}, publisher = {IEEE}, note = {Finalist for best paper award} }
Subsea fauna enumeration using vision-based marine robots
Koreitem, K.; Girdhar, Y.; Cho, W.; Singh, H.; Pineda, J.; Dudek, G.

20162016 13th Conference on Computer and Robot Vision (CRV)
Abstract
Abstract
This paper describes a robotics system for population density estimation of marine organisms and vision-based algorithm for computing the associated population estimates. We focus on benthic fauna, through the use of Seabed AUV to collect benthic imagery, and then employ a support vector machine (SVM) for automated analysis of these images to estimate the population of the fauna of interest. The proposed approach is a significant improvement over existing techniques such as trawling, or manual inspection of images
Topics
coral reef mappinglocalizationmarine biologyslamunderwater navigationunderwater roboticswavelet analysis
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@inproceedings{koreitem2016subsea, title={Subsea fauna enumeration using vision-based marine robots}, author={Koreitem, K. and Girdhar, Y. and Cho, W. and Singh, H. and Pineda, J. and Dudek, G.}, booktitle={2016 13th Conference on Computer and Robot Vision (CRV)}, pages={101--108}, year={2016}, organization={IEEE} }
Texture-aware slam using stereo imagery and inertial information
Manderson; T.; F. Shkurti; G. Dudek

20162016 13th Conference on Computer and Robot Vision (CRV)
Abstract
Abstract
We present a gaze control method that augments an existing stereo and inertial Simultaneous Localization And Mapping (SLAM) system by directing the stereo camera towards feature-rich regions of the scene. Our integrated active SLAM system is based on careful triangulation of visual features, existing successful nonlinear optimization, and visual loop closing frameworks. It relies on the tight coupling of IMU measurements with constraints imposed by visual correspondences from both stereo and motion. Alongside the SLAM
Topics
localizationslamtexture
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@inproceedings{manderson2016texture, title={Texture-aware slam using stereo imagery and inertial information}, author={Manderson, T. and Shkurti, F. and Dudek, G.}, booktitle={2016 13th Conference on Computer and Robot Vision (CRV)}, pages={456--463}, year={2016}, organization={IEEE} }

Towards modeling real-time trust in asymmetric human--robot collaborations

Xu, Anqi; Dudek, Gregory

2016Robotics Research: The 16th International Symposium ISRR

Abstract

We are interested in enhancing the efficiency of human–robot collaborations, especially in “supervisor-worker” settings where autonomous robots work under the supervision of a human operator. We believe that trust serves a critical role in modeling the interactions within these teams, and also in streamlining their efficiency. We propose an operational formulation of human–robot trust on a short interaction time scale, which is tailored to a practical tele-robotics setting. We also report on a controlled user study that collected

Topics

aerial roboticshuman-robot interactiontelecommunicationsteleoperationtrust modeling

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@inproceedings{xu2016towards,
 abstract = {We are interested in enhancing the efficiency of human–robot collaborations, especially in “supervisor-worker” settings where autonomous robots work under the supervision of a human operator. We believe that trust serves a critical role in modeling the interactions within these teams, and also in streamlining their efficiency. We propose an operational formulation of human–robot trust on a short interaction time scale, which is tailored to a practical tele-robotics setting. We also report on a controlled user study that collected},
 author = {Xu, Anqi and Dudek, Gregory},
 booktitle = {Robotics Research: The 16th International Symposium ISRR},
 organization = {Springer},
 pages = {113--129},
 pub_year = {2016},
 title = {Towards modeling real-time trust in asymmetric human--robot collaborations},
 venue = {Robotics Research: The 16th International Symposium …}
}

AEROSTABILES: A new approach to HRI research
St-Onge; David; Reeves; Nicolas; Gigu\`ere; Philippe; Sharf; Inna; Dudek; Gregory; Rekleitis; Ioannis; Br\`eches; Pierre-Yves; Abouzakhm; Patrick; Babin; Philippe

2015Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction (Extended Abstracts)
Abstract
Abstract
Initiated as a research-creation project by professor and artist Nicolas Reeves, the Aerostabile project quickly expanded to include researchers and artists from a wide range of disciplines. Its current phase brings together four robotic and research-creation labs with various expertises in unstable and dynamic environments. The first group, under the direction of professor Inna Sharf, is based at the department of mechanical engineering at University McGill. It works on control and modeling of autonomous blimps for satellite
Topics
aerial roboticshuman-robot interaction
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@inproceedings{St-Onge2015, author = {David St-Onge and Nicolas Reeves and Philippe Gigu\`ere and Inna Sharf and Gregory Dudek and Ioannis Rekleitis and Pierre-Yves Br\`eches and Patrick Abouzakhm and Philippe Babin}, title = {AEROSTABILES: A new approach to HRI research}, booktitle = {Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction (Extended Abstracts)}, year = {2015}, pages = {277--277}, month = {March} }
Autonomous gait selection for energy efficient walking
Manjanna; Sandeep; Gregory Dudek

2015Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '15)
Abstract
Abstract
In this paper, we investigate the question of how a legged robot can walk efficiently by taking advantage of its ability to alter its gait as a function of statistical (large-scale) terrain properties. One of the contributions of this paper is the algorithm to achieve real-time terrain identification and autonomous gait adaptation on a legged robot. We approach this problem by first classifying the terrains based on their proprioceptive responses and identifying the terrain in real-time. Then we choose an optimal gait to best suit the identified terrain type. We
Topics
adaptive controllocalizationterrain identificationwalking robots
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@inproceedings{manjanna2015autonomous, title={Autonomous gait selection for energy efficient walking}, author={Manjanna, Sandeep and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '15)}, pages={5155--5162}, year={2015}, location={Seattle, USA}, month={May} }
Learning legged swimming gaits from experience
Meger; D.; J. C. Gamboa Higuera; A. Xu; P. Giguere; G. Dudek

2015Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '15)best paper nominee
Abstract
Abstract
We present an end-to-end framework for realizing fully automated gait learning for a complex underwater legged robot. Using this framework, we demonstrate that a hexapod flipper-propelled robot can learn task-specific control policies purely from experience data. Our method couples a state-of-the-art policy search technique with a family of periodic low-level controls that are well suited for underwater propulsion. We demonstrate the practical efficacy of tabula rasa learning, that is, learning without the use of any prior knowledge, of
Topics
adaptive controllocalizationreinforcement learningunderwater navigationunderwater robotics
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@inproceedings{meger2015learning, author = {Meger, David and Gamboa Higuera, Juan C. and Xu, A. and Giguere, P. and Dudek, Gregory}, title = {Learning legged swimming gaits from experience}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '15)}, pages = {5155--5162}, year = {2015}, address = {Seattle, USA}, note = {best paper nominee} }
OPTIMo: Online Probabilistic Trust Inference Model for Asymmetric Human-Robot Collaborations
Xu; Anqi; Gregory Dudek

2015Proceedings of the 10th ACM/IEEE International Conference on Human-Robot Interactions (HRI '15)
Abstract
Abstract
We present OPTIMo: an Online Probabilistic Trust Inference Model for quantifying the degree of trust that a human supervisor has in an autonomous robot" worker". Represented as a Dynamic Bayesian Network, OPTIMo infers beliefs over the human's moment-to-moment latent trust states, based on the history of observed interaction experiences. A separate model instance is trained on each user's experiences, leading to an interpretable and personalized characterization of that operator's behaviors and attitudes. Using datasets
Topics
adaptive controlanomaly detectionbayesian inferencebehavior cloninghuman-robot interactionknowledge distillationlocalizationreinforcement learningtelecommunicationstrust modeling
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@inproceedings{xu2015optimo, author = {Anqi Xu and Gregory Dudek}, title = {OPTIMo: Online Probabilistic Trust Inference Model for Asymmetric Human-Robot Collaborations}, booktitle = {Proceedings of the 10th ACM/IEEE International Conference on Human-Robot Interactions (HRI '15)}, pages = {7}, location = {Portland, USA}, month = {March}, year = {2015} }
Robust Environment Mapping Using Flux Skeletons
Rezanejad; Morteza; Samari; Babak; Rekleitis; Ioannis; Siddiqi; Kaleem Dudek; Gregory

20152015 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abstract
Abstract
We consider how to directly extract a road map (also known as a topological representation) of an initially-unknown 2-dimensional environment via an on-line procedure which robustly computes a retraction of its boundaries. While such approaches are well known for their theoretical elegance, computing such representations in practice is complicated when the data is sparse and noisy. In this paper we present the online construction of a topological map and the implementation of a control law for guiding the robot to the nearest unexplored
Topics
complexity boundsenvironment mappinggraph theorylocalizationslam
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@inproceedings{Rezanejad2015, author = {Morteza Rezanejad and Babak Samari and Ioannis Rekleitis and Kaleem Siddiqi and Gregory Dudek}, title = {Robust Environment Mapping Using Flux Skeletons}, booktitle = {2015 IEEE/RSJ International Conference on Intelligent Robots and Systems}, year = {2015}, pages = {Sept 28 - Oct 03}, address = {Hamburg, Germany} }
Towards Autonomous Robotic Coral Reef Health Assessment
Manderson; T.; Meger; D.; Li; J.; Cortes Poza; D.; Dudek; N.; G. Dudek

2015Proceedings of Field and Service Robotics (FSR)
Abstract
Abstract
This paper addresses the automated analysis of coral in shallow reef environments up to 90 ft deep. During a series of robotic ocean deployments, we have collected a data set of coral and non-coral imagery from four distinct reef locations. The data has been annotated by an experienced biologist and presented as a representative challenge for visual understanding techniques. We describe baseline techniques using texture and color features combined with classifiers for two vision sub-tasks: live coral image classification and live coral
Topics
coral reef mappinglocalizationmarine biologyobject recognitionslamtextureunderwater robotics
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@inproceedings{manderson2015autonomous, title={Towards Autonomous Robotic Coral Reef Health Assessment}, author={Manderson, T. and Meger, D. and Li, J. and Cortes Poza, D. and Dudek, N. and Dudek, G.}, booktitle={Proceedings of Field and Service Robotics (FSR)}, address={Toronto, Canada}, year={2015}, month={June 24--26} }
Towards Efficient Collaborations with Trust-Seeking Adaptive Robots
Xu; Anqi; Gregory Dudek

2015Proceedings of the 10th Human-Robot Interaction Pioneers Workshop (HRI Pioneers '15)
Abstract
Abstract
We are interested in asymmetric human-robot teams, where a human supervisor occasionally takes over control to aid an autonomous robot in a given task. Our research aims to optimize team efficiency by improving the robot's task performance, decreasing the human's workload, and building trust in the team. We envision synergistic collaborations where the robot adapts its behaviors dynamically to optimize efficacy, reduce manual interventions, and actively seek for greater trust. We describe recent works that study two
Topics
adaptive controlbehavior cloninghuman-robot interactionreinforcement learningtrust modeling
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@inproceedings{xu2015towards, author = {Anqi Xu and Gregory Dudek}, title = {Towards Efficient Collaborations with Trust-Seeking Adaptive Robots}, booktitle = {Proceedings of the 10th Human-Robot Interaction Pioneers Workshop (HRI Pioneers '15)}, year = {2015}, pages = {2}, address = {Portland, USA}, month = {March} }
Uncertainty Reduction via Heuristic Search Planning on Hybrid Metric/Topological Map
Q. Zhang; I. Rekleitis; G. Dudek

2015Proceedings of Conference on Computer and Robot Vision
Abstract
Abstract
Uncertainty Reduction via Heuristic Search Planning on Hybrid Metric/Topological Map
Topics
complexity boundsgraph theorylocalizationslam
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@inproceedings{zhang2015uncertainty, author = {Q. Zhang and I. Rekleitis and G. Dudek}, title = {Uncertainty Reduction via Heuristic Search Planning on Hybrid Metric/Topological Map}, booktitle = {Proceedings of Conference on Computer and Robot Vision}, year = {2015}, address = {Halifax, NS}, month = {June} }
3D trajectory synthesis and control for a legged swimming robot
Meger; David; Shkurti; Florian; Cortes Poza; David; Giguere; Philippe; Gregory Dudek

2014Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014)
Abstract
Abstract
Inspection and exploration of complex underwater structures requires the development of agile and easy to program platforms. In this paper, we describe a system that enables the deployment of an autonomous underwater vehicle in 3D environments proximal to the ocean bottom. Unlike many previous approaches, our solution: uses oscillating hydrofoil propulsion; allows for stable control of the robot's motion and sensor directions; allows human operators to specify detailed trajectories in a natural fashion; and has been
Topics
coral reef mappinghuman-robot interactionunderwater navigationunderwater robotics
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@inproceedings{Meger2014, author = {David Meger and Florian Shkurti and David Cortes Poza and Philippe Giguere and Gregory Dudek}, title = {3D trajectory synthesis and control for a legged swimming robot}, booktitle = {Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014)}, year = {2014}, address = {Chicago, IL}, month = {Sept.}, pages = {2257--2264} }
Adaptive Parameter EXploration (APEX): Adaptation of robot autonomy from human participation
Xu; Anqi; Kalmbach; Arnold; Gregory Dudek

2014Proc. IEEE International Conference on Robotics and Automation (ICRA 2014)
Abstract
Abstract
The problem of Adaptation from Participation (AfP) aims to improve the efficiency of a human-robot team by adapting a robot's autonomous systems and behaviors based on command-level input from a human supervisor. As a solution to AfP, the Adaptive Parameter EXploration (APEX) algorithm continuously explores the space of all possible parameter configurations for the robot's autonomous system in an online and anytime manner. Guided by information deduced from the human's latest intervening commands, APEX is capable of
Topics
adaptive controlaerial roboticscomplexity boundshuman-robot interactionlocalization
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@inproceedings{xu2014adaptive, title={Adaptive Parameter EXploration (APEX): Adaptation of robot autonomy from human participation}, author={Xu, Anqi and Kalmbach, Arnold and Dudek, Gregory}, booktitle={Proc. IEEE International Conference on Robotics and Automation (ICRA 2014)}, pages={3315--3322}, year={2014}, location={Hong Kong} }
Asymmetric Rendezvous Search at Sea
Meghjani; Malika; Shkurti; Florian; Higuera; Juan Camilo Gamboa; Kalmbach; Arnold; Whitney; David; Gregory Dudek

2014Proc. Conference on Computer and Robot Vision (CRV 2014)
Abstract
Abstract
In this paper we address the rendezvous problem between an autonomous underwater vehicle (AUV) and a passively floating drifter on the sea surface. The AUV's mission is to keep an estimate of the floating drifter's position while exploring the underwater environment and periodically attempting to rendezvous with it. We are interested in the case where the AUV loses track of the drifter, predicts its location and searches for it in the vicinity of the predicted location. We parameterize this search problem with respect to both the uncertainty
Topics
exploration strategieslocalizationrendezvousslamunderwater robotics
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@inproceedings{Meghjani2014, author = {Malika Meghjani and Florian Shkurti and Juan Camilo Gamboa Higuera and Arnold Kalmbach and David Whitney and Gregory Dudek}, title = {Asymmetric Rendezvous Search at Sea}, booktitle = {Proc. Conference on Computer and Robot Vision (CRV 2014)}, pages = {7}, address = {Montreal, Canada}, month = {June}, year = {2014} }

Autonomous adaptive exploration using realtime online spatiotemporal topic modeling

Girdhar; Yogesh; Gigu\`ere; Philippe; Gregory Dudek

2014The International Journal of Robotics Research

Abstract

The exploration of dangerous environments such as underwater coral reefs and shipwrecks is a difficult and potentially life-threatening task for humans, which naturally makes the use of an autonomous robotic system very appealing. This paper presents such an autonomous system, which is capable of autonomous exploration, and shows its use in a series of experiments to collect image data in challenging underwater marine environments. We present novel contributions on three fronts. First, we present an online topic-modeling-based

Topics

coral reef mappingexploration strategiesimage matchinglocalizationslamunderwater navigationunderwater roboticsvideo summaries

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@article{girdhar2014autonomous,
 abstract = {The exploration of dangerous environments such as underwater coral reefs and shipwrecks is a difficult and potentially life-threatening task for humans, which naturally makes the use of an autonomous robotic system very appealing. This paper presents such an autonomous system, which is capable of autonomous exploration, and shows its use in a series of experiments to collect image data in challenging underwater marine environments. We present novel contributions on three fronts. First, we present an online topic-modeling-based},
 author = {Girdhar, Yogesh and Giguere, Philippe and Dudek, Gregory},
 journal = {The International Journal of Robotics Research},
 number = {4},
 pages = {645--657},
 pub_year = {2014},
 publisher = {SAGE Publications Sage UK: London, England},
 title = {Autonomous adaptive exploration using realtime online spatiotemporal topic modeling},
 venue = {The International Journal of …},
 volume = {33}
}

Curiosity Based Exploration for Learning Terrain Models
Girdhar; Yogesh; Whitney; David; Gregory Dudek

2014Proc. IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We present a robotic exploration technique in which the goal is to learn a visual model that can be used to distinguish between different terrains and other visual components in an unknown environment. We use ROST, a realtime online spatiotemporal topic modeling framework to model these terrains using the observations made by the robot, and then use an information theoretic path planning technique to define the exploration path. We conduct experiments with aerial view and underwater datasets with millions of observations and
Topics
localizationpath planningreinforcement learningslamunderwater robotics
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@inproceedings{Girdhar2014, author = {Yogesh Girdhar and David Whitney and Gregory Dudek}, title = {Curiosity Based Exploration for Learning Terrain Models}, booktitle = {Proc. IEEE International Conference on Robotics and Automation (ICRA)}, year = {2014}, pages = {7}, address = {Hong Kong}, month = {May}, eprint = {arXiv:1310.6767} }
Exploring Underwater Environments with Curiosity
Girdhar; Yogesh; Gregory Dudek

2014Proc. Conference on Computer and Robot Vision (CRV 2014)
Abstract
Abstract
This paper presents a novel approach to modeling curiosity in a mobile robot, which is useful for monitoring and adaptive data collection tasks. We use ROST, a real time topic modeling framework to build a semantic perception model of the environment, using which, we plan a path through the locations in the world with high semantic information content. We demonstrate the approach using the Aqua robot in a variety of different scenarios, and find the robot be able to do tasks such as coral reef inspection, diver following, and sea floor
Topics
complexity boundscoral reef mappinggraph theorylocalizationpath planningslamunderwater robotics
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@inproceedings{Girdhar2014, author = {Yogesh Girdhar and Gregory Dudek}, title = {Exploring Underwater Environments with Curiosity}, booktitle = {Proc. Conference on Computer and Robot Vision (CRV 2014)}, pages = {7 pages}, address = {Montreal, Canada}, month = {June}, year = {2014} }
Maximizing visibility in collaborative trajectory planning
Shkurti; Florian; Gregory Dudek

2014Proc. IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
In this paper we address the issue of coordinating the trajectories of two collaborating robots in environments with obstacles so that visibility between them is maximized in the presence of competing constraints. Specifically, we examine the problem of allowing one robot (the “photographer”) to follow another robot (“the subject”) through a planar environment while maintaining visual contact to the maximum degree consistent with an efficient traversal. This problem has numerous applications, for instance in scenarios where communication
Topics
cooperative localizationlocalization
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@inproceedings{shkurti2014maximizing, author = {Florian Shkurti and Gregory Dudek}, title = {Maximizing visibility in collaborative trajectory planning}, booktitle = {Proc. IEEE International Conference on Robotics and Automation (ICRA)}, year = {2014}, pages = {3315--3322}, address = {Hong Kong}, month = {May} }
Multi-agent rendezvous on street networks
Meghjani; Malika; Gregory Dudek

2014Proc. IEEE International Conference on Robotics and Automation (ICRA 2014)
Abstract
Abstract
In this paper we present an algorithm for finding a distance optimal rendezvous location with respect to both initial and target locations of the mobile agents. These agents can be humans or robots, who need to meet and split while performing a collaborative task. Our aim is to embed the meeting process within a background activity such that the agents travel through the rendezvous location while taking the shortest paths to their respective target locations. We analyze this problem in a street network scenario with two agents who are
Topics
localizationpath planningslamtelecommunications
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@inproceedings{meghjani2014multi, author = {Malika Meghjani and Gregory Dudek}, title = {Multi-agent rendezvous on street networks}, booktitle = {Proc. IEEE International Conference on Robotics and Automation (ICRA 2014)}, pages = {5792--5797}, year = {2014}, address = {Hong Kong}, month = {May} }

Special Issue of the Thirteenth International Symposium on Experimental Robotics, 2012

Desai; Jaydev; Gregory Dudek; Oussama Khatib; Vijay Kumar

2014The International Journal of Robotics Research

Abstract

This special issue consists of 12 papers drawn from contributions at the Thirteenth International Symposium on Experimental Robotics in 2012 (ISER'12). ISER is a series of biennial symposia whose goal is to provide the robotics community with a forum for research driven by creative ideas, bold visions, new systems, and novel applications of robotics, emphasizing experimental work. The ISER tradition fosters scholarly work that either addresses validation of theoretical paradigms through careful experimentation or the

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@misc{desai2014special,
 abstract = {This special issue consists of 12 papers drawn from contributions at the Thirteenth International Symposium on Experimental Robotics in 2012 (ISER'12). ISER is a series of biennial symposia whose goal is to provide the robotics community with a forum for research driven by creative ideas, bold visions, new systems, and novel applications of robotics, emphasizing experimental work. The ISER tradition fosters scholarly work that either addresses validation of theoretical paradigms through careful experimentation or the},
 author = {Desai, Jaydev P and Dudek, Gregory and Khatib, Oussama and Kumar, Vijay},
 journal = {The International Journal of Robotics Research},
 number = {4},
 pages = {487--488},
 pub_year = {2014},
 publisher = {SAGE Publications Sage UK: London, England},
 title = {Special Issue of the Thirteenth International Symposium on Experimental Robotics, 2012},
 venue = {… International Journal of …},
 volume = {33}
}

Special Issue of the Thirteenth International Symposium on Experimental Robotics, 2012

Desai; Jaydev; Gregory Dudek; Oussama Khatib; Vijay Kumar

2014The International Journal of Robotics Research

Abstract

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@misc{desai2014special,
 abstract = {This special issue consists of 12 papers drawn from contributions at the Thirteenth International Symposium on Experimental Robotics in 2012 (ISER'12). ISER is a series of biennial symposia whose goal is to provide the robotics community with a forum for research driven by creative ideas, bold visions, new systems, and novel applications of robotics, emphasizing experimental work. The ISER tradition fosters scholarly work that either addresses validation of theoretical paradigms through careful experimentation or the},
 author = {Desai, Jaydev P and Dudek, Gregory and Khatib, Oussama and Kumar, Vijay},
 journal = {The International Journal of Robotics Research},
 number = {4},
 pages = {487--488},
 pub_year = {2014},
 publisher = {SAGE Publications Sage UK: London, England},
 title = {Special Issue of the Thirteenth International Symposium on Experimental Robotics, 2012},
 venue = {… International Journal of …},
 volume = {33}
}

Special issue on robotics: science and systems

Dudek; Gregory; Dieter Fox

2014Autonomous Robots

Abstract

This issue of Autonomous Robots presents journal articles that are based on papers originally presented at the 2013 Robotics Science and Systems conference, held in Berlin, Germany. Although these were selected by a committee to exemplify the best papers presented that year, the decision over which papers to include was a difficult one due to the substantial number of very strong papers in the cohort. While the strength of these papers can be partially attributed to the fact that the conference itself generally attracts strong

Topics

human-robot interaction

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@article{dudek2014special,
 abstract = {This issue of Autonomous Robots presents journal articles that are based on papers originally presented at the 2013 Robotics Science and Systems conference, held in Berlin, Germany. Although these were selected by a committee to exemplify the best papers presented that year, the decision over which papers to include was a difficult one due to the substantial number of very strong papers in the cohort. While the strength of these papers can be partially attributed to the fact that the conference itself generally attracts strong},
 author = {Dudek, Gregory and Fox, Dieter},
 journal = {Autonomous Robots},
 pages = {333--334},
 pub_year = {2014},
 publisher = {Springer},
 title = {Special issue on robotics: science and systems},
 venue = {Autonomous Robots},
 volume = {37}
}

Autonomous Adaptive Underwater Exploration using Online Topic Modeling
Girdhar; Yogesh; Giguere; Philippe; Gregory Dudek

2013Experimental Robotics
Abstract
Abstract
Exploration of underwater environments, such as coral reefs and ship wrecks, is a difficult and potentially dangerous tasks for humans, which naturally makes the use of an autonomous robotic system very appealing. This paper presents such an autonomous system, and shows its use in a series of experiments to collect image data in an underwater marine environment. We presents novel contributions on three fronts. First, we present an online topic-modeling based technique to describe what is being observed using a low
Topics
adaptive controladaptive samplinganomaly detectioncoral reef mappingexploration strategiesimage matchinglocalizationpath planningplace recognitionslamunderwater navigationunderwater roboticsvideo summaries
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@inproceedings{Girdhar2013, author = {Yogesh Girdhar and Philippe Giguere and Gregory Dudek}, title = {Autonomous Adaptive Underwater Exploration using Online Topic Modeling}, booktitle = {Experimental Robotics}, pages = {789--802}, year = {2013}, note = {Presented at the International Symposium on Experimental Robotics (ISER)} }
Autonomous Adaptive Underwater Exploration using Online Topic Modeling
Yogesh Girdhar; Philippe Giguere; Gregory Dudek

2013Experimental Robotics
Abstract
Abstract
Exploration of underwater environments, such as coral reefs and ship wrecks, is a difficult and potentially dangerous tasks for humans, which naturally makes the use of an autonomous robotic system very appealing. This paper presents such an autonomous system, and shows its use in a series of experiments to collect image data in an underwater marine environment. We presents novel contributions on three fronts. First, we present an online topic-modeling based technique to describe what is being observed using a low
Topics
adaptive controladaptive samplinganomaly detectioncoral reef mappingexploration strategiesimage matchinglocalizationpath planningplace recognitionslamunderwater navigationunderwater roboticsvideo summaries
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@inproceedings{Girdhar2013, author = {Yogesh Girdhar and Philippe Giguere and Gregory Dudek}, title = {Autonomous Adaptive Underwater Exploration using Online Topic Modeling}, booktitle = {Experimental Robotics}, pages = {789--802}, year = {2013}, note = {Presented at the International Symposium on Experimental Robotics (ISER)} }
Experimental Robotics: The 13th International Symposium on Experimental Robotics
JP Desai; G Dudek; O Khatib; V Kumar

2013Springer
Abstract
Abstract
The International Symposium on Experimental Robotics (ISER) is a series of bi-annual meetings, which are organized, in a rotating fashion around North America, Europe and Asia/Oceania. The goal of ISER is to provide a forum for research in robotics that focuses on novelty of theoretical contributions validated by experimental results. The meetings are conceived to bring together, in a small group setting, researchers from around the world who are in the forefront of experimental robotics research. This unique reference presents the
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@book{Desai2013, editor = {Jaydev Desai and Gregory Dudek and Oussama Khatib and Vijay Kumar}, title = {Experimental Robotics: The 13th International Symposium on Experimental Robotics}, year = {2013}, publisher = {Springer}, doi = {10.1007/978-3-319-00065-7}, isbn = {978-3-319-00064-0}, isbn = {978-3-319-00065-7 (eBook)}, issn = {1610-742X (electronic)} }
Fair Subdivision of Multirobot Tasks
Gamboa Higuera; Juan Camilo; Gregory Dudek

2013Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We study the problem of distributing a single global task between a group of heterogeneous robots. We view this problem as a fair division game. In this setting, every robot defines a preference function over parts of the task according to its sensing and motion capabilities. These preferences are described by density functions over the task. With such interpretation, we want to find an allocation of the global task that maximizes the probability of task completion. We first formulate the task distribution problem as a fair subdivision problem and
Topics
telecommunications
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@inproceedings{gamboa2013fair, author = {Juan Camilo Gamboa Higuera and Gregory Dudek}, title = {Fair Subdivision of Multirobot Tasks}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, year = {2013}, pages = {6}, address = {Karlsruhe, Germany}, month = {May} }
Ninja Legs: Amphibious One Degree of Freedom Robotic Legs
Dey; Bir Bikram; Manjanna; Sandeep; Gregory Dudek

2013Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '13)
Abstract
Abstract
In this paper we propose a design of a class of robotic legs (known as “Ninja legs”) that enable amphibious operation, both walking and swimming, for use on a class of hexapod robots. Amphibious legs equip the robot with a capability to explore diverse locations in the world encompassing both those that are on the ground as well as underwater. In this paper we work with a hexapod robot of the Aqua vehicle family (based on a body plan first developed by Buehler et al.[1]), which is an amphibious robot that employs legs for
Topics
exploration strategiesunderwater roboticswalking robots
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@inproceedings{dey2013ninja, title={Ninja Legs: Amphibious One Degree of Freedom Robotic Legs}, author={Dey, Bir Bikram and Manjanna, Sandeep and Dudek, Gregory}, booktitle={Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '13)}, year={2013}, address={Tokyo, Japan}, month={November} }
On the complexity of searching for an evader with a faster pursuer
Shkurti; Florian; Gregory Dudek

2013Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
In this paper we examine pursuit-evasion games in which the pursuer has higher speed than the evader. This scenario is motivated by visibility-based pursuit-evasion problems, particularly by the question of what happens when the pursuer loses visual track of the moving evader. In these cases the pursuer has two options for recovering visual contact with the evader: to perform search over the possible locations where the evader might be moving, or to clear the environment, in other words to progressively search it without
Topics
complexity boundsexploration strategieslocalization
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@inproceedings{Shkurti2013, author = {Florian Shkurti and Gregory Dudek}, title = {On the complexity of searching for an evader with a faster pursuer}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, year = {2013}, pages = {6}, address = {Karlsruhe, Germany}, month = {May} }
Unsupervised Environment Recognition and Modeling using Sound Sensing
Kalmbach; Arnold; Girdhar; Yogesh; Gregory Dudek

2013Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We discuss the problem of automatically discovering different acoustic regions in the world, and then labeling the trajectory of a robot using these region labels. We use quantized Mel Frequency Cepstral Coefficients (MFCC) as low level features, and a temporally smoothed variant of Latent Dirichlet Allocation (LDA) to compute both the region models, and most likely region labels associated with each time step in the robot's trajectory. We validate our technique by showing results from two datasets containing sound recorded from 51 and 43
Topics
anomaly detectionbayesian inferencecomplexity boundsenvironment mappinggraph theorylocalizationrobotic collectivesslamsonar and acoustics
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@inproceedings{kalmbach2013unsupervised, title={Unsupervised Environment Recognition and Modeling using Sound Sensing}, author={Kalmbach, Arnold and Girdhar, Yogesh and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, pages={6}, year={2013}, address={Karlsruhe, Germany}, month={May} }
Using Gait Change for Terrain Sensing by Robots
Manjanna; Sandeep; Gigu\`ere; Philippe; Gregory Dudek

2013Proceedings of the 10th International Conference on Computer and Robot Vision (CRV '13)
Abstract
Abstract
In this paper we examine the interplay between terrain classification accuracy and gait in a walking robot, and show how changes in walking speed can be used for terrain-dependent walk optimizations, as well as to enhance terrain identification. The details of a walking gait have a great influence on the performance of locomotive systems and their interaction with the terrain. Most legged robots can benefit from adapting their gait (and specifically walk speed) to the particular terrain on which they are walking. To achieve this, the agent should
Topics
adaptive controlterrain identificationunderwater roboticswalking robots
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@inproceedings{manjanna2013using, title={Using Gait Change for Terrain Sensing by Robots}, author={Manjanna, Sandeep and Gigu{\`e}re, Philippe and Dudek, Gregory}, booktitle={Proceedings of the 10th International Conference on Computer and Robot Vision (CRV '13)}, pages={7}, year={2013}, address={Regina, Canada}, month={May} }
Wide-Speed Autopilot System for a Swimming Hexapod Robot
Gigu\`ere; Philippe; Girdhar; Yogesh; Gregory Dudek

2013Proceedings of the 10th International Conference on Computer and Robot Vision (CRV '13)
Abstract
Abstract
For underwater swimming robots, which use the unconventional method of oscillating flippers for propulsion and control, being able to move stably at various velocities is challenging. This stable motion facilitates navigation, avoids blurring the images taken by a camera motion, and enables longterm observations of specific locations. Previous experiments with our swimming robot Aqua have shown that its autopilot system must adapt the control parameters as a function of speed. The reason is that the dynamics of both the
Topics
adaptive controladaptive samplingcoral reef mappinglocalizationmarine biologyunderwater navigationunderwater robotics
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@inproceedings{Giguere2013, author = {Philippe Gigu\`ere and Yogesh Girdhar and Gregory Dudek}, title = {Wide-Speed Autopilot System for a Swimming Hexapod Robot}, booktitle = {Proceedings of the 10th International Conference on Computer and Robot Vision (CRV '13)}, year = {2013}, pages = {7 pages}, address = {Regina, Canada}, month = {May}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6569178&isnumber=6569168} }
Efficient on-line data summarization using extremum summaries
Girdhar; Yogesh; Gregory Dudek

2012Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We are interested in the task of online summarization of the data observed by a mobile robot, with the goal that these summaries could be then be used for applications such as surveillance, identifying samples to be collected by a planetary rover, and site inspections to detect anomalies. In this paper, we pose the summarization problem as an instance of the well known k-center problem, where the goal is to identify k observations so that the maximum distance of any observation from a summary sample is minimized. We focus on
Topics
anomaly detection
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@inproceedings{Girdhar2012, author = {Yogesh Girdhar and Gregory Dudek}, title = {Efficient on-line data summarization using extremum summaries}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, year = {2012}, month = {May} }
Monitoring Marine Environments using a Team of Heterogeneous Robots
Girdhar; Yogesh; Xu; Anqi; Shkurti; Florian; Gamboa Higuera; Juan Camilo; Meghjani; Malika; Gigu\`ere; Philippe; Rekleitis; Ioannis; Gregory Dudek

2012RSS 2012 Workshop on Robotics for Environmental Monitoring (WREM 2012)
Abstract
Abstract
We present a novel approach for monitoring marine environments by a team of heterogeneous robots, comprising of a fixed-wing aerial vehicle, an autonomous airboat, and a legged underwater robot. The goal is to receive a region of interest from a remote human supervisor, and then using the coordinated effort of the robot team, produce a concise summary consisting of a small number of images, which capture the visual diversity of the region of interest. The summary could then be used by a human supervisor to plan for
Topics
aerial roboticshuman-robot interactionpath planningunderwater robotics
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@inproceedings{Girdhar2012, author = {Yogesh Girdhar and Anqi Xu and Florian Shkurti and Juan Camilo Gamboa Higuera and Malika Meghjani and Philippe Gigu\`ere and Ioannis Rekleitis and Gregory Dudek}, title = {Monitoring Marine Environments using a Team of Heterogeneous Robots}, booktitle = {RSS 2012 Workshop on Robotics for Environmental Monitoring (WREM 2012)}, year = {2012}, address = {Sydney, Australia} }
Multi-Domain Monitoring of Marine Environments Using a Heterogeneous Robot Team
Shkurti; Florian; Xu; Anqi; Meghjani; Malika; Gamboa Higuera; Juan Camilo; Girdhar; Yogesh; Gigu\`ere; Philippe; Dey; Bir Bikram; Li; Jimmy; Kalmbach; Arnold; Prahacs; Chris; Turgeon; Katrine; Rekleitis; Ioannis; Gregory Dudek

2012Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12)
Abstract
Abstract
In this paper we describe a heterogeneous multi-robot system for assisting scientists in environmental monitoring tasks, such as the inspection of marine ecosystems. This team of robots is comprised of a fixed-wing aerial vehicle, an autonomous airboat, and an agile legged underwater robot. These robots interact with off-site scientists and operate in a hierarchical structure to autonomously collect visual footage of interesting underwater regions, from multiple scales and mediums. We discuss organizational and scheduling
Topics
complexity boundscoral reef mappinggraph theorylocalizationunderwater robotics
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@inproceedings{Shkurti2012, author = {Florian Shkurti and Anqi Xu and Malika Meghjani and Juan Camilo Gamboa Higuera and Yogesh Girdhar and Philippe Gigu\`ere and Bir Bikram Dey and Jimmy Li and Arnold Kalmbach and Chris Prahacs and Katrine Turgeon and Ioannis Rekleitis and Gregory Dudek}, title = {Multi-Domain Monitoring of Marine Environments Using a Heterogeneous Robot Team}, booktitle = {Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12)}, year = {2012}, month = {October}, address = {Algarve, Portugal} }
Multi-Robot Exploration and Rendezvous on Graphs
Meghjani; Malika; Gregory Dudek

2012Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12)
Abstract
Abstract
We address the problem of arranging a meeting (or rendezvous) between two or more robots in an unknown bounded topological environment, starting at unknown locations, without any communication. The goal is to rendezvous in minimum time such that the robots can share resources for performing any global task. We specifically consider a global exploration task executed by two or more robots. Each robot explores the environment simultaneously, for a specified time, then selects potential rendezvous locations, where it
Topics
complexity boundsexploration strategiesgraph theorylocalizationreinforcement learningrendezvousslamunderwater robotics
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@inproceedings{Meghjani2012, author = {Malika Meghjani and Gregory Dudek}, title = {Multi-Robot Exploration and Rendezvous on Graphs}, booktitle = {Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12)}, year = {2012}, address = {Algarve, Portugal}, month = {October} }
Socially-Driven Collective Path Planning for Robot Missions
Gamboa Higuera; Juan Camilo; Xu; Anqi; Shkurti; Florian; Gregory Dudek

2012Proceedings of the 9th Canadian Conference on Computer and Robot Vision (CRV '12)
Abstract
Abstract
We address the problem of path planning for robot missions based on waypoints suggested by multiple human users. These users may be operating under distinct mission objectives and hence suggest different locations for the robot to visit. We formulate this problem using a constrained optimization approach by imposing various operational considerations, such as the robot's maximum traversable distance. We then propose an approximative path planning algorithm with parameterized control over the degree of" social fairness" in the selection of
Topics
coral reef mappingexploration strategieshuman-robot interactionmarine biologypath planning
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@inproceedings{GamboaHiguera2012, author = {Juan Camilo Gamboa Higuera and Anqi Xu and Florian Shkurti and Gregory Dudek}, title = {Socially-Driven Collective Path Planning for Robot Missions}, booktitle = {Proceedings of the 9th Canadian Conference on Computer and Robot Vision (CRV '12)}, year = {2012}, pages = {417--424}, address = {Toronto, Canada}, month = {May} }
Trust-Driven Interactive Visual Navigation for Autonomous Robots
Xu; Anqi; Gregory Dudek

2012Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '12)
Abstract
Abstract
We describe a model of “trust” in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human's expectations, with respect to task demands. Our trust model drives an adaptive mechanism that dynamically adjusts the robot's autonomous behaviors, in order to improve the efficiency of the collaborative team. We illustrate this trust-driven methodology through an interactive
Topics
adaptive controlaerial roboticscoral reef mappinghuman-robot interactionlocalizationslamtrust modeling
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@inproceedings{xu2012trust, title={Trust-Driven Interactive Visual Navigation for Autonomous Robots}, author={Xu, Anqi and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '12)}, pages={3922--3929}, year={2012}, organization={IEEE}, address={St. Paul, USA}, month={May} }

A simple tactile probe for surface identification by mobile robots

Gigu\`ere; Philippe; Gregory Dudek

2011IEEE Transactions on Robotics

Abstract

This paper describes a tactile probe designed for surface identification in a context of all-terrain low-velocity mobile robotics. The proposed tactile probe is made of a small metallic rod with a single-axis accelerometer attached near its tip. Surface identification is based on analyzing acceleration patterns induced at the tip of this mechanically robust tactile probe, while it is passively dragged along a surface. A training dataset was collected over ten different indoor and outdoor surfaces. Classification results for an artificial neural network

Topics

localizationslamtactile sensingterrain identification

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@article{giguere2011simple,
 abstract = {This paper describes a tactile probe designed for surface identification in a context of all-terrain low-velocity mobile robotics. The proposed tactile probe is made of a small metallic rod with a single-axis accelerometer attached near its tip. Surface identification is based on analyzing acceleration patterns induced at the tip of this mechanically robust tactile probe, while it is passively dragged along a surface. A training dataset was collected over ten different indoor and outdoor surfaces. Classification results for an artificial neural network},
 author = {Giguere, Philippe and Dudek, Gregory},
 journal = {IEEE Transactions on Robotics},
 number = {3},
 pages = {534--544},
 pub_year = {2011},
 publisher = {IEEE},
 title = {A simple tactile probe for surface identification by mobile robots},
 venue = {IEEE Transactions on Robotics},
 volume = {27}
}

A surprising problem in navigation

Girdhar; Yogesh; Gregory Dudek

2011Vision in 3D Environments

Abstract

A surprising problem in navigation

Topics

complexity bounds

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@incollection{Girdhar2011,
  author    = {Yogesh Girdhar and Gregory Dudek},
  title     = {A surprising problem in navigation},
  booktitle = {Vision in 3D Environments},
  publisher = {Cambridge University Press},
  year      = {2011},
  pages     = {228--252},
  isbn      = {9781107001756}
}

Combining Multi-Robot Exploration and Rendezvous
Meghjani; Malika; Gregory Dudek

2011Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)
Abstract
Abstract
We consider the problem of exploring an unknown environment with a pair of mobile robots. The goal is to make the robots meet (or rendezvous) in minimum time such that there is a maximum speed gain of the exploration task. The key challenge in achieving this goal is to rendezvous with the least possible dependency on communication. This single constraint involves several sub-problems: finding unique potential rendezvous locations in the environment, ranking these locations based on their uniqueness and synchronizing with the
Topics
complexity boundscooperative localizationenvironment mappinglocalizationrendezvousslamunderwater robotics
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@inproceedings{Meghjani2011, author = {Malika Meghjani and Gregory Dudek}, title = {Combining Multi-Robot Exploration and Rendezvous}, booktitle = {Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)}, year = {2011}, pages = {80--85}, address = {St. John's, Newfoundland, Canada}, month = {May} }
Conformative Filter: A Probabilistic Framework for Localization in Reduced Space
Patrick Virie; Gregory Dudek

2011Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)
Abstract
Abstract
Algorithmic problem reduction is a fundamental approach to problem solving in many fields, including robotics. To solve a problem using this scheme, we must reduce the problem into another one for which solutions exist. The reduction function, which infers a conformation between the problem and the solution space, plays an important role in solution evaluation and is sometimes used to transform the solutions into the problem domain. We consider robot path planning in the context of algorithmic problem reduction where a reduction can be
Topics
localizationpath planningslam
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BibTeX
@inproceedings{virie2011conformative, author = {Patrick Virie and Gregory Dudek}, title = {Conformative Filter: A Probabilistic Framework for Localization in Reduced Space}, booktitle = {Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)}, year = {2011}, pages = {24--31}, address = {St. John's, Newfoundland, Canada}, month = {May} }
Feature Tracking Evaluation for Pose Estimation in Underwater Environments
Shkurti; Florian; Rekleitis; Ioannis; Gregory Dudek

2011Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)
Abstract
Abstract
In this paper we present the computer vision component of a 6DOF pose estimation algorithm to be used by an underwater robot. Our goal is to evaluate which feature trackers enable us to accurately estimate the 3D positions of features, as quickly as possible. To this end, we perform an evaluation of available detectors, descriptors, and matching schemes, over different underwater datasets. We are interested in identifying combinations in this search space that are suitable for use in structure from motion algorithms, and more
Topics
localizationslamunderwater navigationunderwater robotics
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@inproceedings{shkurti2011feature, author = {Florian Shkurti and Ioannis Rekleitis and Gregory Dudek}, title = {Feature Tracking Evaluation for Pose Estimation in Underwater Environments}, booktitle = {Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)}, pages = {160--167}, year = {2011}, address = {St. John's, Newfoundland, Canada}, month = {May} }
Fourier Tag: A Smoothly Degradable Fiducial Marker System with Configurable Payload Capacity
Xu; Anqi; Gregory Dudek

2011Proc. Conference on Computer and Robot Vision (CRV '11)
Abstract
Abstract
We describe the design and implementation of a fiducial marker system that encodes data in the frequency spectrum of a synthetic image. This distinctive approach to marker synthesis and data encoding allows for partial data extraction in adverse imaging conditions, and can significantly extend the detection range through graceful data degradation. Additional digital encoding and image construction techniques are used to increase the payload capacity, and also to store 3-D pose information in each fiducial marker. This fiducial marker scheme can
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@inproceedings{xu2011fourier, author = {Anqi Xu and Gregory Dudek}, title = {Fourier Tag: A Smoothly Degradable Fiducial Marker System with Configurable Payload Capacity}, booktitle = {Proc. Conference on Computer and Robot Vision (CRV '11)}, year = {2011}, pages = {40--47}, address = {St. John's, Newfoundland, Canada}, month = {May} }
Graphical State Space Programming: A Visual Programming Paradigm for Robot Task Specification
Li; Jimmy; Xu; Anqi; Gregory Dudek

20112011 IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We describe a framework that combines a software development paradigm, a software visualization technique, and a tool for robot programming. This infrastructure is called" Graphical State Space Programming"(GSSP), and allows robot application programs to be decomposed and visualized within state-dependent views. Our approach simplifies and expedites the programming process for robot routines and behaviors, and we examine the performance improvement that ensues through a set of controlled user studies. The usability
Topics
aerial roboticsanomaly detectionbehavior cloningcomplexity boundspath planning
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@inproceedings{li2011graphical, title={Graphical State Space Programming: A Visual Programming Paradigm for Robot Task Specification}, author={Li, Jimmy and Xu, Anqi and Dudek, Gregory}, booktitle={2011 IEEE International Conference on Robotics and Automation (ICRA)}, pages={4846--4853}, year={2011}, organization={IEEE}, address={Shanghai, China}, month={May} }
MARE: Marine Autonomous Robotic Explorer
Girdhar; Yogesh; Xu; Anqi; Dey; Bir Bikram; Meghjani; Malika; Shkurti; Florian; Rekleitis; Ioannis; Gregory Dudek

2011Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '11)
Abstract
Abstract
We present MARE, an autonomous airboat robot that is suitable for exploration-oriented tasks, such as inspection of coral reefs and shallow seabeds. The combination of this platform's particular mechanical properties and its powerful software framework enables it to function in a multitude of potential capacities, including autonomous surveillance, mapping, and search operations. In this paper we describe two different exploration strategies and their implementation using the MARE platform. First, we discuss the application of an
Topics
coral reef mappingexploration strategieslocalizationslamunderwater robotics
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@inproceedings{Girdhar2011MARE, author = {Yogesh Girdhar and Anqi Xu and Bir Bikram Dey and Malika Meghjani and Florian Shkurti and Ioannis Rekleitis and Gregory Dudek}, title = {MARE: Marine Autonomous Robotic Explorer}, booktitle = {Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '11)}, year = {2011}, pages = {5048--5053}, address = {San Francisco, USA}, doi = {10.1109/IROS.2011.6048582} }
Offline Navigation Summaries
Girdhar; Yogesh; Gregory Dudek

2011Proceedings of the IEEE International Conference on Robotics and Automation (ICRA2011)
Abstract
Abstract
Our objective is to find a small set of images that summarize a robot's visual experience along a path. We present a novel on-line algorithm for this task. This algorithm is based on a new extension to the classical Secretaries Problem. We also present an extension to the idea of Bayesian Surprise, which we then use to measure the fitness of an image as a summary image.
Topics
localizationpath planningslamvideo summaries
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@inproceedings{Girdhar2011, author = {Yogesh Girdhar and Gregory Dudek}, title = {Offline Navigation Summaries}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA2011)}, year = {2011}, pages = {5769--5775}, address = {Shanghai, China}, month = {May 9--13} }
Offline Navigation Summaries
Yogesh Girdhar; Gregory Dudek

2011Proceedings of the IEEE International Conference on Robotics and Automation (ICRA2011)
Abstract
Abstract
Our objective is to find a small set of images that summarize a robot's visual experience along a path. We present a novel on-line algorithm for this task. This algorithm is based on a new extension to the classical Secretaries Problem. We also present an extension to the idea of Bayesian Surprise, which we then use to measure the fitness of an image as a summary image.
Topics
localizationpath planningslamvideo summaries
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@inproceedings{Girdhar2011, author = {Yogesh Girdhar and Gregory Dudek}, title = {Offline Navigation Summaries}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA2011)}, year = {2011}, pages = {5769--5775}, address = {Shanghai, China}, month = {May 9--13} }
Online Visual Vocabularies
Girdhar; Yogesh; Gregory Dudek

2011Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)
Abstract
Abstract
The idea of an online visual vocabulary is proposed. In contrast to the accepted strategy of generating vocabularies offline, using the k-means clustering over all the features extracted form all the images in a dataset, an online vocabulary is dynamic and evolves iteratively over time as new observations are made. Hence, it is much more suitable for online robotic applications, such as exploration, landmark detection, and SLAM, where the future is unknown. We present two different strategies for building online vocabularies. The first
Topics
complexity boundsexploration strategieslocalizationobject recognition
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@inproceedings{Girdhar2011, author = {Yogesh Girdhar and Gregory Dudek}, title = {Online Visual Vocabularies}, booktitle = {Proceedings of the 8th Canadian Conference on Computer and Robot Vision (CRV '11)}, year = {2011}, pages = {191--196}, address = {St. John's, Newfoundland, Canada}, month = {May} }
Optimal Complete Terrain Coverage using an Unmanned Aerial Vehicle
Xu; Anqi; Viriyasuthee; Chatavut; Rekleitis; Ionnis; Gregory Dudek

2011Proceedings of the 2011 IEEE International Conference on Robotics and Automation (ICRA'11)
Abstract
Abstract
We present the adaptation of an optimal terrain coverage algorithm for the aerial robotics domain. The general strategy involves computing a trajectory through a known environment with obstacles that ensures complete coverage of the terrain while minimizing path repetition. We introduce a system that applies and extends this generic algorithm to achieve automated terrain coverage using an aerial vehicle. Ex tensive experimental results in simulation validate the presented system, along with data from over 100 kilometers of
Topics
aerial roboticscomplexity boundsenvironment mappingexploration strategieslocalizationpath planningslam
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@inproceedings{xu2011optimal, title={Optimal Complete Terrain Coverage using an Unmanned Aerial Vehicle}, author={Xu, Anqi and Viriyasuthee, Chatavut and Rekleitis, Ioannis and Dudek, Gregory}, booktitle={Proceedings of the 2011 IEEE International Conference on Robotics and Automation (ICRA'11)}, pages={2513--2519}, year={2011}, organization={IEEE}, address={Shanghai, China}, month={May} }

Scene reconstruction with sparse range data and intensity information

G. Y. Chen; Gregory Dudek; L. A. Torres-Mendez

2011Optical Engineering

Abstract

Scene reconstruction with sparse range data and intensity information

Topics

3d reconstructionlocalizationmarkov random fieldsslam

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@article{Chen2011,
  author    = {G. Y. Chen and Gregory Dudek and L. A. Torres-Mendez},
  title     = {Scene reconstruction with sparse range data and intensity information},
  journal   = {Optical Engineering},
  volume    = {50},
  number    = {9},
  pages     = {097002},
  year      = {2011},
  doi       = {10.1117/1.3617455},
  url       = {http://dx.doi.org/10.1117/1.3617455}
}

Towards Quantitative Modeling of Task Confirmations in Human-Robot Dialog
Sattar; Junaed; Gregory Dudek

2011Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We present a technique for robust human-robot interaction taking into consideration uncertainty in input and task execution costs incurred by the robot. Specifically, this research aims to quantitatively model confirmation feedback, as required by a robot while communicating with a human operator to perform a particular task. Our goal is to model human-robot interaction from the perspective of risk minimization, taking into account errors in communication," risk" involved in performing the required task, and task execution costs
Topics
human-robot interactionteleoperationunderwater robotics
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@inproceedings{sattar2011towards, title={Towards Quantitative Modeling of Task Confirmations in Human-Robot Dialog}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, pages={1957--1963}, year={2011}, address={Shanghai, China}, month={May 9--13} }
Towards Quantitative Modeling of Task Confirmations in Human-Robot Dialog
Sattar; Junaed; Gregory Dudek

2011Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
We present a technique for robust human-robot interaction taking into consideration uncertainty in input and task execution costs incurred by the robot. Specifically, this research aims to quantitatively model confirmation feedback, as required by a robot while communicating with a human operator to perform a particular task. Our goal is to model human-robot interaction from the perspective of risk minimization, taking into account errors in communication," risk" involved in performing the required task, and task execution costs
Topics
human-robot interactionteleoperationunderwater robotics
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@inproceedings{sattar2011towards, title={Towards Quantitative Modeling of Task Confirmations in Human-Robot Dialog}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, pages={1957--1963}, year={2011}, address={Shanghai, China}, month={May 9--13} }
A Vision-Based Boundary Following Framework for Aerial Vehicles
Xu; Anqi; Gregory Dudek

2010Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10)
Abstract
Abstract
We present an integration of classical computer vision techniques to achieve real-time autonomous steering of an unmanned aircraft along the boundary of different regions. Using an unified conceptual framework, we illustrate solutions for tracking coastlines and for following roads surrounded by forests. In particular, we exploit color and texture properties to differentiate between region types in the aforementioned domains. The performance of our system is evaluated using different experimental approaches, which includes a fully
Topics
aerial robotics
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@inproceedings{xu2010vision, title={A Vision-Based Boundary Following Framework for Aerial Vehicles}, author={Xu, Anqi and Dudek, Gregory}, booktitle={Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10)}, pages={81--86}, year={2010}, organization={IEEE}, address={Taipei, Taiwan}, month={October} }
Computational Principles of Mobile Robotics (2nd edition)
Dudek, Gregory; Jenkin, Michael

2010Cambridge University Press
Abstract
Abstract
Computational Principles of Mobile Robotics 2nd edition
Topics
localizationslam
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@book{dudek2024computational, title={Computational Principles of Mobile Robotics (2nd edition)}, author={Dudek, Gregory and Jenkin, Michael}, edition={3rd}, year={2010}, publisher={Cambridge University Press}, pages={450} }
Graphical State-Space Programmability as a Natural Interface for Robotic Control
Sattar; Junaed; Xu; Anqi; Charette; Gabrielle; Gregory Dudek

2010Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA '10)
Abstract
Abstract
We present an interface for controlling mobile robots that combines aspects of graphical trajectory specification and state-based programming. This work is motivated by common tasks executed by our underwater vehicles, although we illustrate a mode of interaction that is applicable to mobile robotics in general. The key aspect of our approach is to provide an intuitive linkage between the graphical visualization of regions of interest in the environment, and activities relevant to these regions. In addition to introducing this novel programming
Topics
complexity boundscomputer graphicscoral reef mappinghuman-robot interactionlocalizationmarine biologyslamtelecommunicationsunderwater robotics
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@inproceedings{sattar2010graphical, author = {Junaed Sattar and Anqi Xu and Gabrielle Charette and Gregory Dudek}, title = {Graphical State-Space Programmability as a Natural Interface for Robotic Control}, booktitle = {Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA '10)}, year = {2010}, pages = {4609--4614}, address = {Anchorage, Alaska, USA}, month = {May} }
ONSUM: A System for Generating Online Navigation Summaries
Girdhar; Yogesh; Gregory Dudek

2010Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2010)Nominee for ICROS best application paper award from 972 accepted papers
Abstract
Abstract
We propose an algorithm for generating navigation summaries. Navigation summaries are a specialization of video summaries, where the focus is on video collected by a mobile robot, on a specified trajectory. We are interested in finding a few images that epitomize the visual experience of a robot as it traverses a terrain. This paper presents a novel approach to generating summaries in form of a set of images, where the decision to include the image in the summary set is made online. Our focus is on the case where the number of observations
Topics
complexity boundscoral reef mappinglocalizationslamunderwater roboticsvideo summaries
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@inproceedings{Girdhar2010, author = {Yogesh Girdhar and Gregory Dudek}, title = {ONSUM: A System for Generating Online Navigation Summaries}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2010)}, year = {2010}, address = {Taipei, Taiwan}, month = {October}, note = {Nominee for ICROS best application paper award from 972 accepted papers} }

Pure topological mapping in mobile robotics

Marinakis; Dimitri; Gregory Dudek

2010IEEE Transactions on Robotics

Abstract

In this paper, we investigate a pure form of the topological mapping problem in mobile robotics. We consider the mapping ability of a robot navigating a graph-like world in which it is able to assign a relative ordering to the edges, leaving a vertex with reference to the edge by which it arrived but is unable to associate a unique label with any vertex or edge. Our work extends and builds upon earlier approaches in this problem domain, which are based on construction of exploration tree of plausible world models. The main contributions of the

Topics

complexity boundsgraph theorylocalizationslam

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@article{marinakis2010pure,
 abstract = {In this paper, we investigate a pure form of the topological mapping problem in mobile robotics. We consider the mapping ability of a robot navigating a graph-like world in which it is able to assign a relative ordering to the edges, leaving a vertex with reference to the edge by which it arrived but is unable to associate a unique label with any vertex or edge. Our work extends and builds upon earlier approaches in this problem domain, which are based on construction of exploration tree of plausible world models. The main contributions of the},
 author = {Marinakis, Dimitri and Dudek, Gregory},
 journal = {IEEE Transactions on Robotics},
 number = {6},
 pages = {1051--1064},
 pub_year = {2010},
 publisher = {IEEE},
 title = {Pure topological mapping in mobile robotics},
 venue = {IEEE Transactions on Robotics},
 volume = {26}
}

Reducing Uncertainty in Human-Robot Interaction: A Cost Analysis Approach
Sattar; Junaed; Gregory Dudek

2010Proceedings of the Twelfth International Symposium on Experimental Robotics (ISER 2010)
Abstract
Abstract
We present a technique for robust human-robot interaction taking into consideration uncertainty in input and task execution costs incurred by the robot. Specifically, this research aims to quantitatively model confirmation feedback, as required by a robot while communicating with a human operator to perform a particular task. Our goal is to model human-robot interaction from the perspective of risk minimization, taking into account errors in communication,“risk” involved in performing the required task, and task execution costs
Topics
human-robot interactionunderwater robotics
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@inproceedings{sattar2010reducing, title={Reducing Uncertainty in Human-Robot Interaction: A Cost Analysis Approach}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proceedings of the Twelfth International Symposium on Experimental Robotics (ISER 2010)}, year={2010}, address={New Delhi and Agra, India}, month={December} }
Telepresence Across the Ocean
Rekleitis; Ioannis; Schoueri; Yasmina; Gigu\`ere; Philippe; Sattar; Junaed; Gregory Dudek

2010Proceedings of the Seventh Canadian Conference on Computer and Robot Vision (CRV 2010)
Abstract
Abstract
We describe the development and deployment of a system for long-distance remote observation of robotic operations. The system we have developed is targeted to exploration, multi-participant interaction, and tele-learning. In particular, we used this system with a robot deployed in an underwater environment in order to produce interactive web-casts of scientific material. The system used a combination of robotic and networking technologies and was deployed and evaluated in a context where students in a classroom were able to
Topics
underwater robotics
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@inproceedings{Rekleitis2010, author = {Ioannis Rekleitis and Yasmina Schoueri and Philippe Gigu\`ere and Junaed Sattar and Gregory Dudek}, title = {Telepresence Across the Ocean}, booktitle = {Proceedings of the Seventh Canadian Conference on Computer and Robot Vision (CRV 2010)}, year = {2010}, pages = {261--268}, address = {Ottawa, Ontario, Canada}, month = {May} }
A Vision-based Control and Interaction Framework for a Legged Underwater Robot
Sattar; Junaed; Gregory Dudek

2009Proc. Sixth Canadian Conference on Robot Vision (CRV)Award for best robotics paper
Abstract
Abstract
We present a vision-based control and interaction framework for mobile robots, and describe its implementation in a legged amphibious robot. The control scheme enables the robot to navigate, follow targets of interest, and interact with human operators. The visual framework presented in this paper enables deployment of the vehicle in underwater environments along with a human scuba diver as the operator, without requiring any external tethered control. We present the current implementation of this framework in our particular family of
Topics
human-robot interactionlocalizationslamunderwater robotics
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@inproceedings{sattar2009vision, title={A Vision-based Control and Interaction Framework for a Legged Underwater Robot}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proc. Sixth Canadian Conference on Robot Vision (CRV)}, pages={329--336}, year={2009}, address={Kelowna, BC, Canada}, note={Award for best robotics paper} }
Auto-correlation wavelet support vector machine
Chen; Guangyi; Gregory Dudek

2009Image Vision Computing
Abstract
Abstract
A support vector machine (SVM) with the auto-correlation of a compactly supported wavelet as a kernel is proposed in this paper. The authors prove that this kernel is an admissible support vector kernel. The main advantage of the auto-correlation of a compactly supported wavelet is that it satisfies the translation invariance property, which is very important for its use in signal processing. Also, we can choose a better wavelet by selecting from different wavelet families for our auto-correlation wavelet kernel. This is because for different
Topics
image matchingwavelet analysis
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@article{chen2009auto, title={Auto-correlation wavelet support vector machine}, author={Chen, Guangyi and Dudek, Gregory}, journal={Image Vision Computing}, volume={27}, number={8}, pages={1040--1046}, year={2009}, publisher={Elsevier}, doi={10.1016/j.imavis.2008.09.006} }
Auto-correlation wavelet support vector machine
Chen; Guangyi; Gregory Dudek

2009Image Vision Computing
Abstract
Abstract
A support vector machine (SVM) with the auto-correlation of a compactly supported wavelet as a kernel is proposed in this paper. The authors prove that this kernel is an admissible support vector kernel. The main advantage of the auto-correlation of a compactly supported wavelet is that it satisfies the translation invariance property, which is very important for its use in signal processing. Also, we can choose a better wavelet by selecting from different wavelet families for our auto-correlation wavelet kernel. This is because for different
Topics
image matchingwavelet analysis
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@article{chen2009auto, title={Auto-correlation wavelet support vector machine}, author={Chen, Guangyi and Dudek, Gregory}, journal={Image Vision Computing}, volume={27}, number={8}, pages={1040--1046}, year={2009}, publisher={Elsevier}, doi={10.1016/j.imavis.2008.09.006} }
Auto-correlation wavelet support vector machine
Chen; G. Y.; Gregory Dudek

2009Image Vision Computing
Abstract
Abstract
A support vector machine (SVM) with the auto-correlation of a compactly supported wavelet as a kernel is proposed in this paper. The authors prove that this kernel is an admissible support vector kernel. The main advantage of the auto-correlation of a compactly supported wavelet is that it satisfies the translation invariance property, which is very important for its use in signal processing. Also, we can choose a better wavelet by selecting from different wavelet families for our auto-correlation wavelet kernel. This is because for different
Topics
image matchingwavelet analysis
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BibTeX
@article{chen2009auto, title={Auto-correlation wavelet support vector machine}, author={Chen, Guangyi and Dudek, Gregory}, journal={Image Vision Computing}, volume={27}, number={8}, pages={1040--1046}, year={2009}, publisher={Elsevier}, doi={10.1016/j.imavis.2008.09.006} }

Clustering sensor data for autonomous terrain identification using time-dependency

Gigu\`ere; Philippe; Gregory Dudek

2009Autonomous Robots

Abstract

In this paper we are interested in autonomous vehicles that can automatically develop terrain classifiers without human interaction or feedback. A key issue is the clustering of time-series data collected by the sensors of a ground-based vehicle moving over several terrain surfaces (eg concrete or soil). In this context, we present a novel off-line windowless clustering algorithm that exploits time-dependency between samples. In terrain coverage, sets of sensory measurements are returned that are spatially, and hence temporally

Topics

localizationterrain identification

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@article{giguere2009clustering,
 abstract = {In this paper we are interested in autonomous vehicles that can automatically develop terrain classifiers without human interaction or feedback. A key issue is the clustering of time-series data collected by the sensors of a ground-based vehicle moving over several terrain surfaces (eg concrete or soil). In this context, we present a novel off-line windowless clustering algorithm that exploits time-dependency between samples. In terrain coverage, sets of sensory measurements are returned that are spatially, and hence temporally},
 author = {Giguere, Philippe and Dudek, Gregory},
 journal = {Autonomous Robots},
 pages = {171--186},
 pub_year = {2009},
 publisher = {Springer},
 title = {Clustering sensor data for autonomous terrain identification using time-dependency},
 venue = {Autonomous Robots},
 volume = {26}
}

Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Pomerantz; Daniel; Gregory Dudek

2009Proceedings of the 22nd Canadian Conference on Artificial Intelligence, Canadian AI 2009
Abstract
Abstract
We use a hierarchical Bayesian approach to model user preferences in different contexts or settings. Unlike many previous recommenders, our approach is content-based. We assume that for each context, a user has a different set of preference weights which are linked by a common,“generic context” set of weights. The approach uses Expectation Maximization (EM) to estimate both the generic context weights and the context specific weights. This improves upon many current recommender systems that do not incorporate context into the
Topics
knowledge distillation
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@inproceedings{pomerantz2009context, title={Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model}, author={Pomerantz, Daniel and Dudek, Gregory}, booktitle={Proceedings of the 22nd Canadian Conference on Artificial Intelligence, Canadian AI 2009}, year={2009}, location={Kelowna, British Columbia, Canada} }

Image stitching with dynamic elements

Mills; Alec; Gregory Dudek

2009Image and Vision Computing

Abstract

This paper presents a new combination of techniques to create pleasing and physically consistent image mosaics despite the presence of moving objects in the scene. The technique uses heuristic seam selection in the intensity and gradient-domains to choose which pixels to use from each image and then blends them smoothly to create the final mosaic. We demonstrate illustrative results obtained by comparing and contrasting our output with that obtained from four representative existing image mosaic systems. One of

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@article{mills2009image,
 abstract = {This paper presents a new combination of techniques to create pleasing and physically consistent image mosaics despite the presence of moving objects in the scene. The technique uses heuristic seam selection in the intensity and gradient-domains to choose which pixels to use from each image and then blends them smoothly to create the final mosaic. We demonstrate illustrative results obtained by comparing and contrasting our output with that obtained from four representative existing image mosaic systems. One of},
 author = {Mills, Alec and Dudek, Gregory},
 journal = {Image and Vision Computing},
 number = {10},
 pages = {1593--1602},
 pub_year = {2009},
 publisher = {Elsevier},
 title = {Image stitching with dynamic elements},
 venue = {Image and Vision Computing},
 volume = {27}
}

Inferring a Probability Distribution Function for the Pose of a Sensor Network using a Mobile Robot
Meger; David; Marinakis; Dimitri; Rekleitis; Ioannis; Gregory Dudek

2009Proc. IEEE International Conference on Robotics and Automation (ICRA2009)
Abstract
Abstract
In this paper we present an approach for localizing a sensor network augmented with a mobile robot which is capable of providing inter-sensor pose estimates through its odometry measurements. We present a stochastic algorithm that samples efficiently from the probability distribution for the pose of the sensor network by employing Rao-Blackwellization and a proposal scheme which exploits the sequential nature of odometry measurements. Our algorithm automatically tunes itself to the problem instance and includes a principled
Topics
localizationsensor networks
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@inproceedings{meger2009inferring, title={Inferring a Probability Distribution Function for the Pose of a Sensor Network using a Mobile Robot}, author={Meger, David and Marinakis, Dimitri and Rekleitis, Ioannis and Dudek, Gregory}, booktitle={Proc. IEEE International Conference on Robotics and Automation (ICRA2009)}, pages={Kobe, Japan}, year={2009}, month={May 12--17} }
Optimal Online Data Sampling or How to Hire the Best Secretaries
Yogesh Girdhar; Gregory Dudek

2009Proceedings of the Sixth Canadian Conference on Computer and Robot Vision
Abstract
Abstract
The problem of online sampling of data, can be seen as a generalization of the classical secretary problem. The goal is to maximize the probability of picking the k highest scoring samples in our data, making the decision to select or reject a sample online. We present a new and simple online algorithm to optimally make this selection. We then apply this algorithm to a sequence of images taken by a mobile robot, with the goal of identifying the most interesting and informative images.
Topics
complexity boundslocalizationslam
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@inproceedings{Girdhar2009, author = {Yogesh Girdhar and Gregory Dudek}, title = {Optimal Online Data Sampling or How to Hire the Best Secretaries}, booktitle = {Proceedings of the Sixth Canadian Conference on Computer and Robot Vision}, year = {2009}, address = {Kelowna, British Columbia, Canada}, month = {May} }
Robust Servo-control for Underwater Robots using Banks of Visual Filters
Sattar; Junaed; Gregory Dudek

2009Proc. IEEE International Conference on Robotics and Automation (ICRA2009)
Abstract
Abstract
We present an application of machine learning to the semi-automatic synthesis of robust servo-trackers for underwater robotics. In particular, we investigate an approach based on the use of Boosting for robust visual tracking of color objects in an underwater environment. To this end, we use AdaBoost, the most common variant of the Boosting algorithm, to select a number of low-complexity but moderately accurate color feature trackers and we combine their outputs. The novelty of our approach lies in the design of this family of weak trackers
Topics
object recognitionunderwater robotics
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@inproceedings{sattar2009robust, title={Robust Servo-control for Underwater Robots using Banks of Visual Filters}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proc. IEEE International Conference on Robotics and Automation (ICRA2009)}, pages={3583--3588}, year={2009}, address={Kobe, Japan}, month={May 12--17} }

Self-calibration of a vision-based sensor network

Marinakis; Dimitri; Gregory Dudek

2009Image and vision computing

Abstract

When a network of vision-based sensors is emplaced in an environment for applications such as surveillance or monitoring the spatial relationships between the sensing units must be inferred or computed for self-calibration purposes. In this paper we describe a technique to solve one aspect of this self-calibration problem: automatically determining the topology and connectivity information of a network of cameras based on a statistical analysis of observed motion in the environment. While the technique can use labels from reliable

Topics

markov chain monte carlosensor networks

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@article{marinakis2009self,
 abstract = {When a network of vision-based sensors is emplaced in an environment for applications such as surveillance or monitoring the spatial relationships between the sensing units must be inferred or computed for self-calibration purposes. In this paper we describe a technique to solve one aspect of this self-calibration problem: automatically determining the topology and connectivity information of a network of cameras based on a statistical analysis of observed motion in the environment. While the technique can use labels from reliable},
 author = {Marinakis, Dimitri and Dudek, Gregory},
 journal = {Image and vision computing},
 number = {1-2},
 pages = {116--130},
 pub_year = {2009},
 publisher = {Elsevier},
 title = {Self-calibration of a vision-based sensor network},
 venue = {Image and vision computing},
 volume = {27}
}

Surface Identification Using Simple Contact Dynamics for Mobile Robots
Gigu\`ere; Philippe; Gregory Dudek

2009Proc. IEEE International Conference on Robotics and Automation (ICRA2009)
Abstract
Abstract
This paper describes an approach to surface identification in the context of mobile robotics, applicable to supervised and unsupervised learning. The identification is based on analyzing the tip acceleration patterns induced in a metallic rod, dragged along a surface that is to be identified. Eight features in time and frequency domains are used for classification. Results show that for ten type of indoor and outdoor surfaces, reliable identification can be achieved (90.0 and 94.6 percent for a 1 and 4 seconds time-window
Topics
anomaly detectionlocalizationtactile sensingterrain identification
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@inproceedings{giguere2009surface, author = {Philippe Gigu\`ere and Gregory Dudek}, title = {Surface Identification Using Simple Contact Dynamics for Mobile Robots}, booktitle = {Proc. IEEE International Conference on Robotics and Automation (ICRA2009)}, year = {2009}, address = {Kobe, Japan}, month = {May 12-17} }
Towards Navigation Summaries: Automated Production of a Synopsis of a Robot Trajectories
G. Dudek; J.-P. Lobos

2009Proc. Conference on Computer and Robot Vision
Abstract
Abstract
In this paper we describe an approach to computing a navigation summary: a visual synopsis of the notable images that characterize a trajectory. We use a combination of PCA and supplementary features to ensure both converge of the trajectory and appearance spaces. The results obtained from a series of experiments are promising and provide us with a method to index and classify video footage from our robot.
Topics
video summaries
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@inproceedings{Dudek2009, author = {G. Dudek and J.-P. Lobos}, title = {Towards Navigation Summaries: Automated Production of a Synopsis of a Robot Trajectories}, booktitle = {Proc. Conference on Computer and Robot Vision}, year = {2009}, pages = {93--100}, doi = {10.1109/CRV.2009.43}, address = {Kelowna, BC, Canada} }
Underwater Human-Robot Interaction via Biological Motion Identification
Sattar; Junaed; Gregory Dudek

2009Proc. Robotics: Science and Systems V
Abstract
Abstract
We present an algorithm for underwater robots to visually detect and track human motion. Our objective is to enable human-robot interaction by allowing a robot to follow behind a human moving in (up to) six degrees of freedom. In particular, we have developed a system to allow a robot to detect, track and follow a scuba diver by using frequencydomain detection of biological motion patterns. The motion of biological entities is characterized by combinations of periodic motions which are inherently distinctive. This is especially true of
Topics
underwater robotics
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@inproceedings{sattar2009underwater, title={Underwater Human-Robot Interaction via Biological Motion Identification}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proc. Robotics: Science and Systems V}, year={2009}, address={Seattle, WA, USA}, month={June-July} }
Unsupervised Learning of Terrain Appearance for Automated Coral Reef Exploration
Gigu\`ere; Philippe; Prahacs; Christopher; Plamondon; Nicolas; Turgeon; Katrine; Gregory Dudek

2009Proceedings of the Sixth Canadian Conference on Computer and Robot Vision
Abstract
Abstract
We describe a navigation and coverage system based on unsupervised learning driven by visual input. Our objective is to allow a robot to remain continuously moving above a terrain of interest using visual feedback to avoid leaving this region. As a particular application domain, we are interested in doing this in open water, but the approach makes few domain-specific assumptions. Specifically, our system employed an unsupervised learning technique to train a k-Nearest Neighbor classifier to distinguish between images of different
Topics
exploration strategieslocalizationunderwater robotics
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@inproceedings{Giguere2009, author = {Philippe Gigu\`ere and Christopher Prahacs and Nicolas Plamondon and Katrine Turgeon and Gregory Dudek}, title = {Unsupervised Learning of Terrain Appearance for Automated Coral Reef Exploration}, booktitle = {Proceedings of the Sixth Canadian Conference on Computer and Robot Vision}, year = {2009}, address = {Kelowna, British Columbia, Canada}, month = {May} }
A Boosting Approach to Visual Servo-Control of an Underwater Robot
Sattar; Junaed; Gregory Dudek

2008Proceedings of the 11th International Symposium on Experimental Robotics, ISER
Abstract
Abstract
We present an application of the ensemble learning algorithm in the area of visual tracking and servoing. In particular, we investigate an approach based on the Boosting technique for robust visual tracking of color objects in an underwater environment. To this end, we use AdaBoost, the most common variant of the Boosting algorithm, to select a number of low-complexity but moderately accurate color feature trackers and we combine their outputs. From a significantly large number of “weak” color trackers, the training process selects those
Topics
complexity boundslocalizationunderwater robotics
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@inproceedings{sattar2008boosting, author = {Junaed Sattar and Gregory Dudek}, title = {A Boosting Approach to Visual Servo-Control of an Underwater Robot}, booktitle = {Proceedings of the 11th International Symposium on Experimental Robotics, ISER}, year = {2008}, address = {Athens, Greece}, month = {July} }
A Natural Gesture Interface for Operating Robotic Systems
Xu; Anqi; Sattar; Junaed; Gregory Dudek

2008Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
A gesture-based interaction framework is presented for controlling mobile robots. This natural interaction paradigm has few physical requirements, and thus can be deployed in many restrictive and challenging environments. We present an implementation of this scheme in the control of an underwater robot by an on-site human operator. The operator performs discrete gestures using engineered visual targets, which are interpreted by the robot as parametrized actionable commands. By combining the symbolic alphabets resulting
Topics
gesture-based interactionhuman-robot interactionlocalizationunderwater robotics
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@inproceedings{xu2008natural, title={A Natural Gesture Interface for Operating Robotic Systems}, author={Xu, Anqi and Sattar, Junaed and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, pages={3557--3563}, year={2008}, location={Pasadena, California, USA} }
Clustering Sensor Data for Terrain Identification using a Windowless Algorithm
Gigu\`ere; Philippe; Gregory Dudek

2008Proc. Robotics Science and System (RSS)
Abstract
Abstract
in autonomous systems that can automatically develop terrain A key issue is clustering of sensor data from the same terrain on data collected from a mobile robot enables robust terrain
Topics
terrain identification
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@inproceedings{giguere2008clustering, title={Clustering Sensor Data for Terrain Identification using a Windowless Algorithm}, author={Gigu{\`e}re, Philippe and Dudek, Gregory}, booktitle={Proc. Robotics Science and System (RSS)}, year={2008}, month={June}, address={Zurich, Switzerland} }
Clustering Sensor Data for Terrain Identification using a Windowless Algorithm
Gigu\`ere; Philippe; Gregory Dudek

2008Proc. Robotics Science and System (RSS)
Abstract
Abstract
in autonomous systems that can automatically develop terrain A key issue is clustering of sensor data from the same terrain on data collected from a mobile robot enables robust terrain
Topics
terrain identification
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@inproceedings{giguere2008clustering, title={Clustering Sensor Data for Terrain Identification using a Windowless Algorithm}, author={Gigu{\`e}re, Philippe and Dudek, Gregory}, booktitle={Proc. Robotics Science and System (RSS)}, year={2008}, month={June}, address={Zurich, Switzerland} }
Clustering Sensor Data for Terrain Identification using a Windowless Algorithm
Giguère, Philippe; Dudek, Gregory

2008Proc. Robotics Science and System (RSS)
Abstract
Abstract
in autonomous systems that can automatically develop terrain A key issue is clustering of sensor data from the same terrain on data collected from a mobile robot enables robust terrain
Topics
terrain identification
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BibTeX
@inproceedings{giguere2008clustering, title={Clustering Sensor Data for Terrain Identification using a Windowless Algorithm}, author={Gigu{\`e}re, Philippe and Dudek, Gregory}, booktitle={Proc. Robotics Science and System (RSS)}, year={2008}, month={June}, address={Zurich, Switzerland} }
Digital Television at Home: Satellite, Cable and Over-The-Air
Dudek; Gregory

2008Y1D Books
Abstract
Abstract
Digital Television at Home: Satellite, Cable and Over-The-Air
Topics
telecommunications
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@book{dudek2008digital, author = {Gregory Dudek}, title = {Digital Television at Home: Satellite, Cable and Over-The-Air}, year = {2008}, publisher = {Y1D Books}, isbn = {978-9809915-0-5} }
Enabling Autonomous Capabilities in Underwater Robotics
Sattar; Junaed; Chiu; Olivia; Rekleitis; Ioannis; Gigu\`ere; Philippe; Mills; Alec; Plamondon; Nicolas; Prahacs; Chris; Girdhar; Yogesh; Nahon; Meyer; Lobos; John-Paul; Gregory Dudek

2008Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Underwater operations present unique challenges and opportunities for robotic applications. These can be attributed in part to limited sensing capabilities, and to locomotion behaviours requiring control schemes adapted to specific tasks or changes in the environment. From enhancing teleoperation procedures, to providing high-level instruction, all the way to fully autonomous operations, enabling autonomous capabilities is fundamental for the successful deployment of underwater robots. This paper presents an overview of the approaches used
Topics
coral reef mappinglocalizationslamteleoperationterrain identificationunderwater robotics
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@inproceedings{sattar2008enabling, title={Enabling Autonomous Capabilities in Underwater Robotics}, author={Sattar, Junaed and Chiu, Olivia and Rekleitis, Ioannis and Gigu{\`e}re, Philippe and Mills, Alec and Plamondon, Nicolas and Prahacs, Chris and Girdhar, Yogesh and Nahon, Meyer and Lobos, John-Paul and Dudek, Gregory}, booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={pp. 3628--3634}, year={2008}, month={September}, address={Nice, France} }

Inter-image statistics for 3d environment modeling

Torres-Mendez; Luz Abril; Gregory Dudek

2008International journal of computer vision

Abstract

In this article we present a method for automatically recovering complete and dense depth maps of an indoor environment by fusing incomplete data for the 3D environment modeling problem. The geometry of indoor environments is usually extracted by acquiring a huge amount of range data and registering it. By acquiring a small set of intensity images and a very limited amount of range data, the acquisition process is considerably simplified, saving time and energy consumption. In our method, the intensity and partial range data are

Topics

3d reconstructionenvironment mappinglocalizationslam

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@article{torres2008inter,
 abstract = {In this article we present a method for automatically recovering complete and dense depth maps of an indoor environment by fusing incomplete data for the 3D environment modeling problem. The geometry of indoor environments is usually extracted by acquiring a huge amount of range data and registering it. By acquiring a small set of intensity images and a very limited amount of range data, the acquisition process is considerably simplified, saving time and energy consumption. In our method, the intensity and partial range data are},
 author = {Torres-M{\'e}ndez, Luz A and Dudek, Gregory},
 journal = {International journal of computer vision},
 pages = {137--158},
 pub_year = {2008},
 publisher = {Springer},
 title = {Inter-image statistics for 3d environment modeling},
 venue = {International journal of computer vision},
 volume = {79}
}

Occam's Razor applied to network topology inference

Marinakis; Dimitri; Gregory Dudek

2008IEEE Transactions on Robotics

Abstract

We present a method for inferring the topology of a sensor network given nondiscriminating observations of activity in the monitored region. This is accomplished based on no prior knowledge of the relative locations of the sensors and weak assumptions regarding environmental conditions. Our approach employs a two-level reasoning system made up of a stochastic expectation maximization algorithm and a higher level search strategy employing the principle of Occam's Razor to look for the simplest solution explaining the

Topics

complexity boundslocalizationsensor networksslam

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@article{marinakis2008occam,
 abstract = {We present a method for inferring the topology of a sensor network given nondiscriminating observations of activity in the monitored region. This is accomplished based on no prior knowledge of the relative locations of the sensors and weak assumptions regarding environmental conditions. Our approach employs a two-level reasoning system made up of a stochastic expectation maximization algorithm and a higher level search strategy employing the principle of Occam's Razor to look for the simplest solution explaining the},
 author = {Marinakis, Dimitri and Dudek, Gregory},
 journal = {IEEE Transactions on Robotics},
 number = {2},
 pages = {293--306},
 pub_year = {2008},
 publisher = {IEEE},
 title = {Occam's Razor applied to network topology inference},
 venue = {IEEE Transactions on Robotics},
 volume = {24}
}

Sensor-based behavior control for an autonomous underwater vehicle
Dudek, Gregory; Giguere, Philippe; Sattar, Junaed

2008Experimental Robotics: The 10th International Symposium on Experimental Robotics
Abstract
Abstract
In this paper, we present behaviors and interaction modes for a small underwater robot. In particular, we address some challenging issues arising from the underwater environment: visual processing, interactive communication with an underwater crew, and finally orientation and motion of the vehicle through a hovering mode. The visual processing consist of target tracking using various techniques (color blob, color histogram and mean shift). The underwater communication is achieved through printed cards with virtual markers
Topics
behavior cloningcooperative localizationcoral reef mappinggesture-based interactionlocalizationmarine biologyobject recognitionpath planningreinforcement learningslamtelecommunicationsteleoperationunderwater robotics
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@inproceedings{dudek2008sensor, abstract = {In this paper, we present behaviors and interaction modes for a small underwater robot. In particular, we address some challenging issues arising from the underwater environment: visual processing, interactive communication with an underwater crew, and finally orientation and motion of the vehicle through a hovering mode. The visual processing consist of target tracking using various techniques (color blob, color histogram and mean shift). The underwater communication is achieved through printed cards with virtual markers}, author = {Dudek, Gregory and Giguere, Philippe and Sattar, Junaed}, booktitle = {Experimental Robotics: The 10th International Symposium on Experimental Robotics}, organization = {Springer}, pages = {267--276}, pub_year = {2008}, title = {Sensor-based behavior control for an autonomous underwater vehicle}, venue = {Experimental Robotics: The 10th …} }
Sensor-based behavior control for an autonomous underwater vehicle
Sattar; Junaed; Gigu\`ere; Philippe; Gregory Dudek

2008Experimental Robotics: The 10th International Symposium on Experimental Robotics
Abstract
Abstract
In this paper, we present behaviors and interaction modes for a small underwater robot. In particular, we address some challenging issues arising from the underwater environment: visual processing, interactive communication with an underwater crew, and finally orientation and motion of the vehicle through a hovering mode. The visual processing consist of target tracking using various techniques (color blob, color histogram and mean shift). The underwater communication is achieved through printed cards with virtual markers
Topics
behavior cloningcooperative localizationcoral reef mappinggesture-based interactionlocalizationmarine biologyobject recognitionpath planningreinforcement learningslamtelecommunicationsteleoperationunderwater robotics
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@inproceedings{dudek2008sensor, abstract = {In this paper, we present behaviors and interaction modes for a small underwater robot. In particular, we address some challenging issues arising from the underwater environment: visual processing, interactive communication with an underwater crew, and finally orientation and motion of the vehicle through a hovering mode. The visual processing consist of target tracking using various techniques (color blob, color histogram and mean shift). The underwater communication is achieved through printed cards with virtual markers}, author = {Dudek, Gregory and Giguere, Philippe and Sattar, Junaed}, booktitle = {Experimental Robotics: The 10th International Symposium on Experimental Robotics}, organization = {Springer}, pages = {267--276}, pub_year = {2008}, title = {Sensor-based behavior control for an autonomous underwater vehicle}, venue = {Experimental Robotics: The 10th …} }
A Visual Language for Robot Control and Programming: A Human-Interface Study
Sattar; Junaed; Xu; Anqi; Gregory Dudek

2007Proceedings of the IEEE International Conference of Robotics and Automation (ICRA)
Abstract
Abstract
We describe an interaction paradigm for controlling a robot using hand gestures. In particular, we are interested in the control of an underwater robot by an on-site human operator. Under this context, vision-based control is very attractive, and we propose a robot control and programming mechanism based on visual symbols. A human operator presents engineered visual targets to the robotic system, which recognizes and interprets them. This paper describes the approach and proposes a specific gesture language called" RoboChat"
Topics
cooperative localizationgesture-based interactionhuman-robot interactionlocalizationunderwater robotics
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@inproceedings{sattar2007visual, author = {Junaed Sattar and Anqi Xu and Gregory Dudek}, title = {A Visual Language for Robot Control and Programming: A Human-Interface Study}, booktitle = {Proceedings of the IEEE International Conference of Robotics and Automation (ICRA)}, year = {2007}, address = {Rome, Italy}, month = {April}, pages = {2507--2513} }

Aqua: An amphibious autonomous robot

Gigu\`ere; P.; Prahacs; C.; Saunderson; S.; Sattar; J.; Torres-Mendez; L.-A.; Jenkin; M.; German; A.; Hogue; A.; Ripsman; A.; Zacher; J.; Milios; E.; Liu; H.; Zhang; P.; Buehler; M.; Georgiades; C.; Gregory Dudek

2007Computer

Abstract

AQUA, an amphibious robot that swims via the motion of its legs rather than using thrusters and control surfaces for propulsion, can walk along the shore, swim along the surface in open water, or walk on the bottom of the ocean. The vehicle uses a variety of sensors to estimate its position with respect to local visual features and provide a global frame of reference

Topics

exploration strategieslocalizationslamunderwater navigationunderwater roboticswalking robots

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@article{dudek2007aqua,
 abstract = {AQUA, an amphibious robot that swims via the motion of its legs rather than using thrusters and control surfaces for propulsion, can walk along the shore, swim along the surface in open water, or walk on the bottom of the ocean. The vehicle uses a variety of sensors to estimate its position with respect to local visual features and provide a global frame of reference},
 author = {Dudek, Gregory and Giguere, Philippe and Prahacs, Chris and Saunderson, Shane and Sattar, Junaed and Torres-Mendez, Luz-Abril and Jenkin, Michael and German, Andrew and Hogue, Andrew and Ripsman, Arlene and others},
 journal = {Computer},
 number = {1},
 pages = {46--53},
 pub_year = {2007},
 publisher = {IEEE},
 title = {Aqua: An amphibious autonomous robot},
 venue = {Computer},
 volume = {40}
}

Hybrid Inference for Sensor Network Localization using a Mobile Robot
Marinakis; Dimitri; Meger; David; Rekleitis; Ioannis; Gregory Dudek

2007Proceedings of the National Conference on Artificial Intelligence (AAAI)
Abstract
Abstract
In this paper, we consider a hybrid solution to the sensor network position inference problem, which combines a real-time filtering system with information from a more expensive, global inference procedure to improve accuracy and prevent divergence. Many online solutions for this problem make use of simplifying assumptions, such as Gaussian noise models and linear system behaviour and also adopt a filtering strategy which may not use available information optimally. These assumptions allow near real-time inference
Topics
localizationmarkov chain monte carloslam
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@inproceedings{marinakis2007hybrid, title={Hybrid Inference for Sensor Network Localization using a Mobile Robot}, author={Marinakis, Dimitri and Meger, David and Rekleitis, Ioannis and Dudek, Gregory}, booktitle={Proceedings of the National Conference on Artificial Intelligence (AAAI)}, year={2007}, address={Vancouver, Canada}, month={July} }
Learning Network Topology from Simple Sensor Data
Marinakis; Dimitri; Gigu\`ere; Philippe; Gregory Dudek

200720th Canadian Conference on Artificial Intelligence
Abstract
Abstract
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this problem, our technique operates on timestamp free observational data; ie no timing information is exploited by our algorithm except the ordering. We first give a theoretical analysis of this version of the problem, and then we show that by considering a sliding window over the observations, the problem can be re-formulated as a version of set
Topics
complexity boundsgraph theorylocalizationsensor networksslamunderwater robotics
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@inproceedings{marinakis2007learning, title={Learning Network Topology from Simple Sensor Data}, author={Marinakis, Dimitri and Gigu{\`e}re, Philippe and Dudek, Gregory}, booktitle={20th Canadian Conference on Artificial Intelligence}, year={2007}, address={Montreal, Canada} }

Randomized algorithms for minimum distance localization

Rao; Malvika; Sue Whitesides; Gregory Dudek

2007The International Journal of Robotics Research

Abstract

The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2 D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several different locations. The goal, therefore, is to determine the robot's true initial location while minimizing the distance traveled by the robot

Topics

complexity boundsenvironment mappinggraph theorylocalizationpath planningslam

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@article{rao2007randomized,
 abstract = {The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2 D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several different locations. The goal, therefore, is to determine the robot's true initial location while minimizing the distance traveled by the robot},
 author = {Rao, Malvika and Dudek, Gregory and Whitesides, Sue},
 journal = {The International Journal of Robotics Research},
 number = {9},
 pages = {917--933},
 pub_year = {2007},
 publisher = {Sage Publications Sage UK: London, England},
 title = {Randomized algorithms for minimum distance localization},
 venue = {The International Journal of …},
 volume = {26}
}

Randomized algorithms for minimum distance localization

Rao; Malvika; Sue Whitesides; Gregory Dudek

2007The International Journal of Robotics Research

Abstract

Topics

complexity boundsenvironment mappinggraph theorylocalizationpath planningslam

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@article{rao2007randomized,
 abstract = {The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2 D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several different locations. The goal, therefore, is to determine the robot's true initial location while minimizing the distance traveled by the robot},
 author = {Rao, Malvika and Dudek, Gregory and Whitesides, Sue},
 journal = {The International Journal of Robotics Research},
 number = {9},
 pages = {917--933},
 pub_year = {2007},
 publisher = {Sage Publications Sage UK: London, England},
 title = {Randomized algorithms for minimum distance localization},
 venue = {The International Journal of …},
 volume = {26}
}

Randomized algorithms for minimum distance localization

Rao; Malvika; Whitesides; Sue; Gregory Dudek

2007The International Journal of Robotics Research

Abstract

Topics

complexity boundsenvironment mappinggraph theorylocalizationpath planningslam

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BibTeX

@article{rao2007randomized,
 abstract = {The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2 D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several different locations. The goal, therefore, is to determine the robot's true initial location while minimizing the distance traveled by the robot},
 author = {Rao, Malvika and Dudek, Gregory and Whitesides, Sue},
 journal = {The International Journal of Robotics Research},
 number = {9},
 pages = {917--933},
 pub_year = {2007},
 publisher = {Sage Publications Sage UK: London, England},
 title = {Randomized algorithms for minimum distance localization},
 venue = {The International Journal of …},
 volume = {26}
}

Topological Mapping through Distributed, Passive Sensors
Marinakis; Dimitri; Gregory Dudek

2007Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI07)
Abstract
Abstract
In this paper we address the problem of inferring the topology, or inter-node navigability, of a sensor network given non-discriminating observations of activity in the environment. By exploiting motion present in the environment, our approach is able to recover a probabilistic model of the sensor network connectivity graph and the underlying traffic trends. We employ a reasoning system made up of a stochastic Expectation Maximization algorithm and a higher level search strategy employing the principle of Occam's Razor to look for the
Topics
complexity boundsgraph theorysensor networks
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@inproceedings{marinakis2007topological, title={Topological Mapping through Distributed, Passive Sensors}, author={Marinakis, Dimitri and Dudek, Gregory}, booktitle={Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI07)}, pages={2147--2152}, year={2007}, address={Hyderabad, India} }
Topological Mapping with Weak Sensory Data
Marinakis; Dimitri; Gregory Dudek

2007Proceedings of the National Conference on Artificial Intelligence (AAAI)
Abstract
Abstract
In this paper, we consider the exploration of topological environments by a robot with weak sensory capabilities. We assume only that the robot can recognize when it has reached a vertex, and can assign a cyclic ordering to the edges leaving a vertex with reference to the edge it arrived from. Given this limited sensing capability, and without the use of any markers or additional information, we will show that the construction of a topological map is still feasible. This is accomplished through both the exploration strategy which is designed to
Topics
complexity boundsexploration strategiesgraph theorylocalizationslam
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@inproceedings{marinakis2007topological, title={Topological Mapping with Weak Sensory Data}, author={Marinakis, Dimitri and Dudek, Gregory}, booktitle={Proceedings of the National Conference on Artificial Intelligence (AAAI)}, year={2007}, address={Vancouver, Canada}, month={July} }
Where is your dive buddy: Tracking scuba divers using spatio-temporal features
Sattar; Junaed; Gregory Dudek

2007Proc. of the IEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Where is your dive buddy: Tracking scuba divers using spatio-temporal features
Topics
complexity boundsgraph theorylocalizationslamunderwater navigationunderwater robotics
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@inproceedings{sattar2007dive, title={Where is your dive buddy: Tracking scuba divers using spatio-temporal features}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proc. of the IEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={3654--3659}, year={2007}, address={San Diego, California, USA}, month={October-November} }
A Practical Algorithm for Network Topology Inference
Marinakis; Dimitri; Gregory Dudek

2006Proceedings of the IEEE International Conference on Robotics and Automation (ICRA06)
Abstract
Abstract
When a network of robots or static sensors is emplaced in an environment, the spatial relationships between the sensing units must be inferred or computed for most key applications. In this paper we present a Monte Carlo expectation maximization algorithm for recovering the connectivity information (ie topological map) of a network using only detection events from deployed sensors. The technique is based on stochastically reconstructing samples of plausible agent trajectories allowing for the possibility of
Topics
complexity boundsgraph theorylocalizationsensor networks
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@inproceedings{marinakis2006practical, title={A Practical Algorithm for Network Topology Inference}, author={Marinakis, Dimitri and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA06)}, pages={3108--3115}, year={2006}, organization={IEEE}, address={Orlando, Florida}, month={May} }

Autonomous Mobile Robot Mapping of a Camera Sensor Network

Meger; David; Rekleitis; Ioannis; Gregory Dudek

2006Proc. 8th International Symposium on Distributed Autonomous Robotic Systems (DARS)

Abstract

Topics

complexity boundslocalizationslam

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@inproceedings{meger2006autonomous,
  title={Autonomous Mobile Robot Mapping of a Camera Sensor Network},
  author={Meger, David and Rekleitis, Ioannis and Dudek, Gregory},
  booktitle={Proc. 8th International Symposium on Distributed Autonomous Robotic Systems (DARS)},
  year={2006}
}

Characterization and Modeling of Rotational Responses for an Oscillating Foil Underwater Robot
Gigu\`ere; Philippe; Prahacs; Chris; Gregory Dudek

2006Proc. IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
In order to better understand the behavior of the underwater robot developed at our laboratory, a simple but relatively good model of the underwater behavior of the robot had to be developed. In order to be useful for model-based control techniques onboard the robot, the model had to have low computing requirements, yet be complex enough to capture the transient response of the robot. To achieve this, a system identification approach was taken by first capturing the robot response to various inputs, and then matching them to a simple
Topics
adaptive controlunderwater robotics
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@inproceedings{giguere2006characterization, title={Characterization and Modeling of Rotational Responses for an Oscillating Foil Underwater Robot}, author={Gigu{\`e}re, Philippe and Prahacs, Chris and Dudek, Gregory}, booktitle={Proc. IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS)}, pages={October}, year={2006}, address={Beijing, China} }
Environment Identification for a Running Robot Using Inertial and Actuator Cues
Gigu\`ere; Philippe; Prahacs; Chris; Saunderson; Shane; Gregory Dudek

2006Proc. Robotics Science and System (RSS)
Abstract
Abstract
Environment Identification for a Running Robot Using Inertial and Actuator Cues
Topics
adaptive controllocalizationslam
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@inproceedings{giguere2006environment, title={Environment Identification for a Running Robot Using Inertial and Actuator Cues}, author={Gigu{\`e}re, Philippe and Prahacs, Chris and Saunderson, Shane and Dudek, Gregory}, booktitle={Proc. Robotics Science and System (RSS)}, year={2006}, month={August}, address={Philadelphia, U.S.A} }
Fourier tags: Smoothly degradable fiducial markers for use in human-robot interaction
Sattar; Junaed; Bourque; Eric; Gigu\`ere; Philippe; Gregory Dudek

2006Proceedings of the Canadian Conference on Computer and Robot Vision (CRV06)
Abstract
Abstract
In this paper we introduce the Fourier tag, a synthetic fiducial marker used to visually encode information and provide controllable positioning. The Fourier tag is a synthetic target akin to a bar-code that specifies multi-bit information which can be efficiently and robustly detected in an image. Moreover, the Fourier tag has the beneficial property that the bit string it encodes has variable length as a function of the distance between the camera and the target. This follows from the fact that the effective resolution decreases as an effect of
Topics
human-robot interactionlocalization
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@inproceedings{sattar2006fourier, author = {Junaed Sattar and Eric Bourque and Philippe Gigu\`ere and Gregory Dudek}, title = {Fourier tags: Smoothly degradable fiducial markers for use in human-robot interaction}, booktitle = {Proceedings of the Canadian Conference on Computer and Robot Vision (CRV06)}, year = {2006}, pages = {22--29}, address = {Quebec City, Quebec} }

Gone swimmin'[seagoing robots]

Theberge, M; Dudek, G

2006IEEE spectrum

Abstract

This paper describes a mechanical hexapod designed by a research group from McGill University. Called Aqua, it is latest in a series of seagoing robots. With six rotating flippers, this machine is amphibious, capable of both walking and swimming. The group aims to develop an underwater vehicle that can autonomously explore and collect data in aquatic environments while surviving the harsh saltwater conditions and often turbulent waters of the open sea

Topics

underwater robotics

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@article{theberge2006gone,
 abstract = {This paper describes a mechanical hexapod designed by a research group from McGill University. Called Aqua, it is latest in a series of seagoing robots. With six rotating flippers, this machine is amphibious, capable of both walking and swimming. The group aims to develop an underwater vehicle that can autonomously explore and collect data in aquatic environments while surviving the harsh saltwater conditions and often turbulent waters of the open sea},
 author = {Theberge, M and Dudek, G},
 journal = {IEEE spectrum},
 number = {6},
 pages = {38--43},
 pub_year = {2006},
 publisher = {IEEE},
 title = {Gone swimmin'[seagoing robots]},
 venue = {IEEE spectrum},
 volume = {43}
}

Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
Garden, Mat; Dudek, Gregory

2006Proceedings of the National Conference on Artificial Intelligence (AAAI)
Abstract
Abstract
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit item semantics. Recommender systems typically use techniques from collaborative filtering, in which proximity measures between users are formulated to generate recommendations, or content-based filtering, in which users are compared directly to items. Our approach uses similarity measures between users, but also directly measures the attributes of items that
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@inproceedings{garden2006mixed, title={Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features}, author={Garden, Mat and Dudek, Gregory}, booktitle={Proceedings of the National Conference on Artificial Intelligence (AAAI)}, year={2006}, address={Boston, MA}, month={July} }
On the Performance of Color Tracking Algorithms for Underwater Robots under Varying Lighting and Visibility
Sattar; Junaed; Gregory Dudek

2006Proceedings of the IEEE International Conference on Robotics and Automation (ICRA06)
Abstract
Abstract
We consider the use of visual target tracking for autonomous steering of an underwater robot. In this context, we consider a performance comparison for three key visual tracking algorithms used for servo control. We present a comparative study of the performance in underwater environments of three tracking algorithms that are widely used in vision applications. Variations in illumination, suspended particles and a resulting reduction in visibility hinders vision systems from performing satisfactorily in marine environments; at
Topics
underwater robotics
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@inproceedings{sattar2006performance, title={On the Performance of Color Tracking Algorithms for Underwater Robots under Varying Lighting and Visibility}, author={Sattar, Junaed and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA06)}, pages={3550--3555}, year={2006}, address={Orlando, Florida} }
Probabilistic Self-Localization for Sensor Networks
Dimitri Marinakis; Dimitri; Gregory Dudek

2006Proc. of the AAAI National Conference on Artificial Intelligence
Abstract
Abstract
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel instances of Markov Chain Monte Carlo (MCMC). By combining estimates drawn from these parallel chains, we build up a representation of the underlying probability distribution function (PDF) for the network pose. Our approach includes sensor data incrementally in order to avoid local minima and is shown to produce meaningful results efficiently. We return
Topics
localizationmarkov chain monte carlosensor networks
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@inproceedings{Marinakis2006, author = {Dimitri Marinakis and Gregory Dudek}, title = {Probabilistic Self-Localization for Sensor Networks}, booktitle = {Proc. of the AAAI National Conference on Artificial Intelligence}, year = {2006}, month = {July}, address = {Boston, Massachusetts, USA} }
RRT-Plan: a Randomized Algorithm for STRIPs planning
Burfoot; Daniel; Joelle Pineau; Gregory Dudek

2006Proc. of the International Conference on Automated Planning and Scheduling (ICAPS06)
Abstract
Abstract
We propose a randomized STRIPS planning algorithm called RRT-Plan. This planner is inspired by the idea of Rapidly exploring Random Trees, a concept originally designed for use in continuous path planning problems. Issues that arise in the conversion of RRTs from continuous to discrete spaces are discussed, and several additional mechanisms are proposed to improve performance. Our experimental results indicate that RRT-Plan is competitive with the state of the art in STRIPS planning.
Topics
complexity boundspath planning
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@inproceedings{burfoot2006rrt, title={RRT-Plan: a Randomized Algorithm for STRIPs planning}, author={Burfoot, Daniel and Pineau, Joelle and Dudek, Gregory}, booktitle={Proc. of the International Conference on Automated Planning and Scheduling (ICAPS06)}, year={2006}, address={Cumbria, UK}, month={June} }

Simultaneous planning, localization, and mapping in a camera sensor network

Rekleitis; Ioannis; Meger; David; Gregory Dudek

2006Robotics and Autonomous Systems

Abstract

In this paper we examine issues of localization, exploration, and planning in the context of a hybrid robot/camera-network system. We exploit the ubiquity of camera networks to use them as a source of localization data. Since the Cartesian position of the cameras in most networks is not known accurately, we consider the issue of how to localize such cameras. To solve this hybrid localization problem, we divide it into a local problem of camera-parameter estimation combined with a global planning and navigation problem. We solve the local

Topics

complexity boundscooperative localizationexploration strategiesgenerative aigraph theorylocalizationsensor networksslam

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@article{rekleitis2006simultaneous,
 abstract = {In this paper we examine issues of localization, exploration, and planning in the context of a hybrid robot/camera-network system. We exploit the ubiquity of camera networks to use them as a source of localization data. Since the Cartesian position of the cameras in most networks is not known accurately, we consider the issue of how to localize such cameras. To solve this hybrid localization problem, we divide it into a local problem of camera-parameter estimation combined with a global planning and navigation problem. We solve the local},
 author = {Rekleitis, Ioannis and Meger, David and Dudek, Gregory},
 journal = {Robotics and Autonomous Systems},
 number = {11},
 pages = {921--932},
 pub_year = {2006},
 publisher = {Elsevier},
 title = {Simultaneous planning, localization, and mapping in a camera sensor network},
 venue = {Robotics and Autonomous Systems},
 volume = {54}
}

Statistics of Visual and Partial Depth Data for Mobile Robot Environment Modeling
Torres-Mendez; Luz Abril; Gregory Dudek

2006Proc. Mexican International Conference on Artificial Intelligence (MICAI)
Abstract
Abstract
In mobile robotics, the inference of the 3D layout of large-scale indoor environments is a critical problem for achieving exploration and navigation tasks. This article presents a framework for building a 3D model of an indoor environment from partial data using a mobile robot. The modeling of a large-scale environment involves the acquisition of a huge amount of range data to extract the geometry of the scene. This task is physically demanding and time consuming for many real systems. Our approach overcomes this problem by allowing a
Topics
3d reconstruction
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@inproceedings{Torres-Mendez2006, author = {Luz Abril Torres-Mendez and Gregory Dudek}, title = {Statistics of Visual and Partial Depth Data for Mobile Robot Environment Modeling}, booktitle = {Proc. Mexican International Conference on Artificial Intelligence (MICAI)}, year = {2006}, month = {November} }
Urban Position Estimation from One Dimensional Visual Cues
Johns; Derek; Gregory Dudek

2006Proceedings of the Canadian Conference on Computer and Robot Vision (CRV06)
Abstract
Abstract
We consider the problem of vision-based position estimation in urban environments. In particular, we are interested in position estimation from visual cues, but using only limited computational resources. Our particular solution to this problem is based on representing the variability of the" horizon" of the cityscape when seen from within the city; that is, the outlines of the rooftops of adjacent buildings. By encoding the image using only such a one-dimensional contour, we obtain an image encoding that is exceedingly compact. This, in
Topics
telecommunications
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@inproceedings{johns2006urban, author = {Derek Johns and Gregory Dudek}, title = {Urban Position Estimation from One Dimensional Visual Cues}, booktitle = {Proceedings of the Canadian Conference on Computer and Robot Vision (CRV06)}, year = {2006}, pages = {22--29}, address = {Quebec City, Quebec}, month = {June} }

A Visual Servoing System for an Aquatic Swimming Robot

Sattar; Junaed; Gigu\`ere; Philippe; Prahacs; Chris; Gregory Dudek

2005Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Abstract

A Visual Servoing System for an Aquatic Swimming Robot

Topics

underwater robotics

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@inproceedings{sattar2005visual,
  title={A Visual Servoing System for an Aquatic Swimming Robot},
  author={Sattar, Junaed and Gigu{\`e}re, Philippe and Prahacs, Chris and Dudek, Gregory},
  booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={1483--1488},
  year={2005},
  address={Edmonton, Alberta, Canada},
  month={August}
}

A Visually Guided Swimming Robot

Jenkin; Michael; Prahacs; Chris; Hogue; Andrew; Sattar; Junaed; Gigu\`ere; Philippe; German; Andrew; Liu; Hui; Saunderson; Shane; Ripsman; Arlene; Simhon; Saul; Torres-Mendez; Luz Abril; Milios; Evangelos; Zhang; Pifu; Ioannis Rekleitis; Gregory Dudek

2005Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Abstract

A Visually Guided Swimming Robot

Topics

localizationslamunderwater robotics

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@inproceedings{jenkin2005visually,
  author    = {Michael Jenkin and Chris Prahacs and Andrew Hogue and Junaed Sattar and Philippe Gigu\`ere and Andrew German and Hui Liu and Shane Saunderson and Arlene Ripsman and Saul Simhon and Luz Abril Torres-Mendez and Evangelos Milios and Pifu Zhang and Ioannis Rekleitis and Gregory Dudek},
  title     = {A Visually Guided Swimming Robot},
  booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year      = {2005},
  pages     = {1749--1754},
  address   = {Edmonton, Alberta, Canada},
  month     = {August}
}

Auto-correlation wavelet support vector machine and its applications to regression

Chen; Guangyi; Gregory Dudek

2005Proc. of Canadian Conference on Computer and Robot Vision (CRV 2005)

Abstract

Auto-correlation wavelet support vector machine and its applications to regression

Topics

wavelet analysis

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@inproceedings{chen2005auto,
  title={Auto-correlation wavelet support vector machine and its applications to regression},
  author={Chen, Guangyi and Dudek, Gregory},
  booktitle={Proc. of Canadian Conference on Computer and Robot Vision (CRV 2005)},
  pages={246--252},
  year={2005},
  doi={10.1109/CRV.2005.19},
  address={Victoria, Canada}
}

Automated Calibration of a Camera Sensor Network
Rekleitis; Ioannis; Gregory Dudek

2005Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
In this paper we present a new approach for the online calibration of a camera sensor network. This is the first step towards fully exploiting the potential for collaboration between mobile robots and static sensors sharing the same network. In particular we propose an approach for extracting the 3D pose of each camera in a common reference frame, with the help of a mobile robot. The camera poses can then be used to further refine the robot pose or to perform other tracking tasks. The analytical formulation of the problem of pose recovery
Topics
cooperative localizationlocalizationsensor networksslam
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@inproceedings{Rekleitis2005, author = {Ioannis Rekleitis and Gregory Dudek}, title = {Automated Calibration of a Camera Sensor Network}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2005}, pages = {401--406}, address = {Edmonton, Alberta, Canada}, month = aug }
Kinematic Variables Estimation using Eye-in-Hand Robot Camera System
Verma; Siddarth; Inna Sharf; Gregory Dudek.

2005Proc. The 2nd Canadian Conference on Computer and Robot Vision
Abstract
Abstract
Vision-based motion variable estimation has been an area of intensive interest, especially for emerging applications in space robotics such as satellite maintenance, refueling and the removal of space debris. For each of these tasks, accurate kinematic motion estimates of an object are required before a robot can approach or interact with the object. In this paper, a technique is presented for autonomous identification of an object against a cluttered background and simultaneous estimation of kinematic variables of the object undergoing
Topics
object recognition
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@inproceedings{verma2005kinematic, title={Kinematic Variables Estimation using Eye-in-Hand Robot Camera System}, author={Verma, Siddarth and Sharf, Inna and Dudek, Gregory}, booktitle={Proc. The 2nd Canadian Conference on Computer and Robot Vision}, pages={550--557}, year={2005}, address={Victoria, BC}, month={May} }
Learning Sensor Network Topology through Monte Carlo Expectation Maximization
Marinakis; Dimitri; Fleet; David; Gregory Dudek

2005Proc. IEEE Intl. Conf. on Robotics and Automation
Abstract
Abstract
We consider the problem of inferring sensor positions and a topological (ie qualitative) map of an environment given a set of cameras with non-overlapping fields of view. In this way, without prior knowledge of the environment nor the exact position of sensors within the environment, one can infer the topology of the environment, and common traffic patterns within it. In particular, we consider sensors stationed at the junctions of the hallways of a large building. We infer the sensor connectivity graph and the travel times between sensors
Topics
complexity boundsenvironment mappinggraph theorylocalizationmarkov chain monte carlosensor networks
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@inproceedings{marinakis2005learning, title={Learning Sensor Network Topology through Monte Carlo Expectation Maximization}, author={Marinakis, Dimitri and Dudek, Gregory}, booktitle={Proc. IEEE Intl. Conf. on Robotics and Automation}, pages={4581--4587}, year={2005}, organization={IEEE}, address={Barcelona, Spain}, month={April} }
Semantic feedback for hybrid recommendations in Recommendz
Garden; Matthew; Gregory Dudek

2005Proceedings of the IEEE International Conference on e-Technology, e-Commerce, and e-Service (EEE05)
Abstract
Abstract
In this paper we discuss the Recommendz recommender system. This domain-independent system combines the advantages of collaborative and content-based filtering in a novel way. By allowing users to provide feedback not only about an item as a whole, but also properties of an item that motivated their opinion, increased performance seems to be achieved. The features used to describe items are specified by the users of the system rather than predetermined using manual knowledge-engineering. We describe a method for combining
Topics
domain adaptation
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@inproceedings{garden2005semantic, title={Semantic feedback for hybrid recommendations in Recommendz}, author={Garden, Matthew and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on e-Technology, e-Commerce, and e-Service (EEE05)}, pages={}, year={2005}, address={Hong Kong, China}, month={March} }
Topology Inference for a Vision-Based Sensor Network
Marinakis; Dimitri; Gregory Dudek

2005Proc. of Canadian Conference on Computer and Robot Vision (CRV 2005)Winner of best paper in the Robotics Category
Abstract
Abstract
In this paper we describe a technique to infer the topology and connectivity information of a network of cameras based on observed motion in the environment. While the technique can use labels from reliable cameras systems, the algorithm is powerful enough to function using ambiguous tracking data. The method requires no prior knowledge of the relative locations of the cameras and operates under very weak environmental assumptions. Our approach stochastically samples plausible agent trajectories based on a delay model that allows for
Topics
complexity boundssensor networks
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@inproceedings{marinakis2005topology, author = {Dimitri Marinakis and Gregory Dudek}, title = {Topology Inference for a Vision-Based Sensor Network}, booktitle = {Proc. of Canadian Conference on Computer and Robot Vision (CRV 2005)}, year = {2005}, address = {Victoria, Canada}, month = {May}, note = {Winner of best paper in the Robotics Category} }

Using Wavelets with Support Vector Machines for Recognition

Chen; Guangyi; Gregory Dudek

2005Proc. of Canadian Conference on Computer and Robot Vision (CRV 2005)

Abstract

Using Wavelets with Support Vector Machines for Recognition

Topics

wavelet analysis

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@inproceedings{chen2005using,
  title={Using Wavelets with Support Vector Machines for Recognition},
  author={Chen, Guangyi and Dudek, Gregory},
  booktitle={Proc. of Canadian Conference on Computer and Robot Vision (CRV 2005)},
  year={2005},
  address={Victoria, Canada},
  month={May}
}

Analogical Path Planning
Simhon; Saul; Gregory Dudek

2004Proceedings of the National Conference on Artificial Intelligence (AAAI)
Abstract
Abstract
We present a probabilistic method for path planning that considers trajectories constrained by both the environment and an ensemble of restrictions or preferences on preferred motions for a moving robot. Our system learns constraints and preference biases on a robot's motion from examples, and then synthesizes behaviors that satisfy these constraints. This behavior can encompass motions that satisfy diverse requirements such as a sweep pattern for floor coverage, or, in particular in our experiments, satisfy restrictions on the
Topics
localizationpath planningreinforcement learningslam
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@inproceedings{simhon2004analogical, author = {Saul Simhon and Gregory Dudek}, title = {Analogical Path Planning}, booktitle = {Proceedings of the National Conference on Artificial Intelligence (AAAI)}, year = {2004}, address = {San Jose, CA}, month = {July}, pages = {6} }
AQUA: an aquatic walking robot
Georgiades; C.; German; A.; Hogue; A.; Liu; H.; Prahacs; C.; Ripsman; A.; Sim; R.; Torres; L.-A.; Zhang; P.; Buehler; M.; Jenkin; M.; Milios; E.; Gregory Dudek

2004Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
This paper describes an underwater walking robotic system being developed under the name AQUA, the goals of the AQUA project, the overall hardware and software design, the basic hardware and sensor packages that have been developed, and some initial experiments. The robot is based on the RHex hexapod robot and uses a suite of sensing technologies, primarily based on computer vision and INS, to allow it to navigate and map clear shallow-water environments. The sensor-based navigation and mapping algorithms
Topics
localizationslamunderwater navigationunderwater roboticswalking robots
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@inproceedings{georgiades2004aqua, title={AQUA: an aquatic walking robot}, author={Georgiades, C. and German, A. and Hogue, A. and Liu, H. and Prahacs, C. and Ripsman, A. and Sim, R. and Torres, L.-A. and Zhang, P. and Buehler, M. and Jenkin, M. and Milios, E. and Dudek, Gregory}, booktitle={Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS)}, year={2004}, location={Sendai, Japan} }
Inter-image Statistics for Scene Reconstruction
Torres-Mendez; Luz-Abril; Marco; Paul Di; Gregory Dudek

2004First Canadian Conference on Computer and Robot Vision
Abstract
Abstract
This paper developed prior work which incrementally completes a sparse depth map based on inter-image statistics information. In that prior work, we have observed that pixel ordering of the incremental recovery is critical to the quality of the final results. In this paper we demonstrate improved performance using an information-driven recovery policy to determine this ordering. We have also observed that the reconstruction across depth discontinuities was often problematic as there was comparatively little constraint for
Topics
3d reconstructionmarkov random fields
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@inproceedings{Torres-Mendez2004, author = {Luz-Abril Torres-Mendez and Paul Di Marco and Gregory Dudek}, title = {Inter-image Statistics for Scene Reconstruction}, booktitle = {First Canadian Conference on Computer and Robot Vision}, year = {2004}, address = {London, ON}, pages = {6} }
Online Control Policy Optimization for Minimizing Map Uncertainty During Exploration
Sim; Robert; Roy; Nicholas; Gregory Dudek

2004Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Abstract
Abstract
Tremendous progress has been made recently in simultaneous localization and mapping of unknown environments. Using sensor and odometry data from an exploring mobile robot, it has become much easier to build high-quality globally consistent maps of many large, real-world environments. To date, however, relatively little attention has been paid to the controllers used to build these maps. Existing exploration strategies usually attempt to cover the largest amount of unknown space as quickly as possible. Few strategies exist for
Topics
exploration strategiesslam
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@inproceedings{sim2004online, title={Online Control Policy Optimization for Minimizing Map Uncertainty During Exploration}, author={Sim, Robert and Roy, Nicholas and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, pages={6}, year={2004}, address={New Orleans, LA}, month={April} }
Pen Stroke Extraction and Refinement using Learned Models
Simhon; Saul; Gregory Dudek

2004Proc. Eurographics Workshop on Sketch-Based Interfaces and Modeling
Abstract
Abstract
This paper presents a smart interface that automatically extracts and refines pen strokes from images of hand drawn sketches. The interface allows users to digitize hand-drawn material such sketches of flowcharts, cartoons or other pen based drawings and automatically isolate and refine the individual strokes making up the sketch. First, we present a method for extracting pen strokes based on learned constraints on curves. The approach consists of using a training set that shows good examples of curves and how a user would
Topics
computer graphicsdeep learningobject recognition
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@inproceedings{simhon2004pen, author = {Saul Simhon and Gregory Dudek}, title = {Pen Stroke Extraction and Refinement using Learned Models}, booktitle = {Proc. Eurographics Workshop on Sketch-Based Interfaces and Modeling}, year = {2004}, address = {Grenoble, France}, month = {August} }
Procedural Texture Matching and Transformation
Bourque; Eric; Gregory Dudek

2004Computer Graphics Forum
Abstract
Abstract
We present a technique for creating a smoothly varying sequence of procedural textures that interpolates between arbitrary input samples of texture. This texture transformation uses a library of procedural shaders and selects the correct shaders and associated parameters to accomplish the task. In general, selecting a procedural texture from a library, or finding the correct parameters to produce a smooth texture transition can be complex and time consuming. We propose a strategy for automating this process. While superficially this
Topics
computer graphicstexture
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@inproceedings{bourque2004procedural, author = {Eric Bourque and Gregory Dudek}, title = {Procedural Texture Matching and Transformation}, booktitle = {Proc. Eurographics 2004}, year = {2004}, month = {August}, pages = {8}, journal = {Computer Graphics Forum} }
Reconstruction of 3D Models from Intensity Images and Partial Depth
Torres-Mendez; Luz-Abril; Gregory Dudek

2004Proceedings of the National Conference on Artificial Intelligence (AAAI)
Abstract
Abstract
This paper addresses the probabilistic inference of geometric structures from images. Specifically, of synthesizing range data to enhance the reconstruction of a 3D model of an indoor environment by using video images and (very) partial depth information. In our method, we interpolate the available range data using statistical inferences learned from the concurrently available video images and from those (sparse) regions where both range and intensity information is available. The spatial relationships between the variations in intensity
Topics
3d reconstruction
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@inproceedings{Torres-Mendez2004, author = {Luz-Abril Torres-Mendez and Gregory Dudek}, title = {Reconstruction of 3D Models from Intensity Images and Partial Depth}, booktitle = {Proceedings of the National Conference on Artificial Intelligence (AAAI)}, year = {2004}, address = {San Jose, CA}, month = {July}, pages = {6} }
Self-Organizing Visual Maps
Sim; Robert; Gregory Dudek

2004Proceedings of the National Conference on Artificial Intelligence (AAAI)
Abstract
Abstract
This paper deals with automatically learning the spatial distribution of a set of images. That is, given a sequence of images acquired from well-separated locations, how can they be arranged to best explain their genesis? The solution to this problem can be viewed as an instance of robot mapping although it can also be used in other contexts. We examine the problem where only limited prior odometric information is available, employing a feature-based method derived from a probabilistic pose estimation framework. Initially, a set of
Topics
complexity boundsgraph theorylocalizationslam
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@inproceedings{sim2004self, title={Self-Organizing Visual Maps}, author={Sim, Robert and Dudek, Gregory}, booktitle={Proceedings of the National Conference on Artificial Intelligence (AAAI)}, pages={6}, year={2004}, address={San Jose, CA}, month={July} }
Sketch Interpretation and Refinement using Statistical Models
Simhon; Saul; Gregory Dudek

2004Proc. Eurographics Symposium on Rendering
Abstract
Abstract
We present a system for generating 2D illustrations from hand drawn outlines consisting of only curve strokes. A user can draw a coarse sketch and the system would automatically augment the shape, thickness, color and surrounding texture of the curves making up the sketch. The styles for these refinements are learned from examples whose semantics have been pre-classified. There can be several styles applicable on a curve and the system automatically identifies which one to use and how to use it based on a curve's shape and its
Topics
anomaly detectioncomputer graphicscurvaturegenerative aiknowledge distillationshapetexturevariational methodsvisual agnosia
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@inproceedings{Simhon2004, author = {Saul Simhon and Gregory Dudek}, title = {Sketch Interpretation and Refinement using Statistical Models}, booktitle = {Proc. Eurographics Symposium on Rendering}, year = {2004} }
Statistical Inference and Synthesis in the Image Domain for Mobile Robot Environment Modeling
Luz Abril Torres-Mendez; Gregory Dudek

2004Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We address the problem of computing dense range maps of indoor locations using only intensity images and partial depth. We allow a mobile robot to navigate the environment, take some pictures and few range data. Our method is based on interpolating the existing range data using statistical inferences learned from the available intensity image and from those (sparse) regions where both range and intensity information is present. The spatial relationships between the variations in intensity and range can be efficiently captured by the
Topics
environment mappinglocalizationmarkov random fieldsslam
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@inproceedings{Torres-Mendez2004, author = {Luz Abril Torres-Mendez and Gregory Dudek}, title = {Statistical Inference and Synthesis in the Image Domain for Mobile Robot Environment Modeling}, booktitle = {Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS)}, year = {2004}, address = {Sendai, Japan} }
Statistics in the Image Domain for Mobile Robot Environment Modeling
Torres-Mendez; Luz Abril; Gregory Dudek

2004Proc. 4th International Symposium of Robotics and Automation
Abstract
Abstract
This paper addresses the problem of estimating dense range maps of indoor locations using only intensity images and sparse partial depth information. Unlike shape-fromshading, we infer the relationship between intensity and range data and use it to produce a complete depth map. We extend prior work by incorporating geometric information from the available range data, specifically, we add surface normal information to reconstruct surfaces whose variations are not captured in the initial range measurements. In addition, the order on which
Topics
localizationmarkov random fieldsslam
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@inproceedings{Torres-Mendez2004, author = {Luz Abril Torres-Mendez and Gregory Dudek}, title = {Statistics in the Image Domain for Mobile Robot Environment Modeling}, booktitle = {Proc. 4th International Symposium of Robotics and Automation}, year = {2004}, address = {Queretaro, Mexico}, month = {August} }
Comparing image-based localization methods
Sim; Robert; Gregory Dudek

2003Proc. of the International Joint Conference on Artificial Intelligence (IJCAI)
Abstract
Abstract
This paper compares alternative approaches to pose estimation using visual cues from the environment. We examine approaches that derive pose estimates from global image properties, such as principal components analysis (PCA) versus from local image properties, commonly referred to as landmarks. We also consider the failure-modes of the different methods. Our work is validated with experimental results.
Topics
place recognition
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@inproceedings{sim2003comparing, title={Comparing image-based localization methods}, author={Sim, Robert and Dudek, Gregory}, booktitle={Proc. of the International Joint Conference on Artificial Intelligence (IJCAI)}, pages={3}, year={2003}, address={Acapulco, Mexico}, month={Aug} }
Effective Exploration Strategies for the Construction of Visual Maps
Sim; Robert; Gregory Dudek

2003Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We consider the effect of exploration policy in the context of the autonomous construction of a visual map of an unknown environment. Like other concurrent mapping and localization (CML) tasks, odometric uncertainty poses the problem of introducing distortions into the map which are difficult to correct without costly on-line or post-processing algorithms. Our problem is further compounded by the implicit nature of the visual map representation, which is designed to accommodate a wide variety of visual phenomena without assuming a
Topics
localization
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@inproceedings{sim2003effective, title={Effective Exploration Strategies for the Construction of Visual Maps}, author={Sim, Robert and Dudek, Gregory}, booktitle={Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)}, pages={8}, year={2003}, address={Las Vegas, NV}, month={Oct} }
Examining Exploratory Trajectories for Minimizing Map Uncertainty
Sim; Robert; Gregory Dudek

2003Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) workshop on Reasoning with Uncertainty in Robotics (RUR)
Abstract
Abstract
We examine the problem of minimizing uncertainty in the automated construction of a visual map of an unknown environment. Our work is motivated by the idea that a robot's exploration policy can impact the accuracy of the resulting map, and we seek to examine the behavior of a set of policies that exhibit a trade-off between accuracy and efficiency. We are further motivated by the specific requirements of our map representation, which learns a set of implicit models of visual features. Such a representation precludes the instantiation of
Topics
complexity boundsenvironment mappinggraph theorylocalizationreinforcement learningslam
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@inproceedings{sim2003examining, title={Examining Exploratory Trajectories for Minimizing Map Uncertainty}, author={Sim, Robert and Dudek, Gregory}, booktitle={Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) workshop on Reasoning with Uncertainty in Robotics (RUR)}, pages={8}, year={2003}, address={Acapulco, Mexico}, month={Aug} }
Experiments in Free-Space Triangulation Using Cooperative Localization
Rekleitis; Ioannis; Milios; Evangelos; Gregory Dudek

2003Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
This paper presents a first detailed case study of collaborative exploration of a substantial environment. We use a pair of cooperating robots to test multi-robot environment mapping algorithms based on triangulation of free space. The robots observe one another using a robot tracking sensor based on laser range sensing (LIDAR). The environment mapping itself is accomplished using sonar sensing. The results of this mapping are compared to those obtained using scanning laser range sensing and the scan matching algorithm. We
Topics
cooperative localizationenvironment mappinglocalizationslamsonar and acoustics
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@inproceedings{Rekleitis2003, author = {Ioannis Rekleitis and Evangelos Milios and Gregory Dudek}, title = {Experiments in Free-Space Triangulation Using Cooperative Localization}, booktitle = {Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)}, year = {2003}, address = {Las Vegas, NV}, month = {Oct.}, pages = {8} }
On User Recommendations Based on Multiple Cues
Garden; Matthew; Gregory Dudek

2003Proc. IEEE WI/IAT 2003 Workshop on Applications, Products and Services of Web-Based Support Systems (in conjunction with IEEE/WIC International Conference on Web Intelligence)
Abstract
Abstract
In this paper we present an overview of a recommender system that attempts to predict user preferences based on several sources including prior choices and selected user-defined features. By using a combination of collaborative filtering and semantic features, we hope to provide performance superior to either alone. Further, our set of semantic features is acquired and updated using a learning-based procedure that avoids the need for manual knowledgeengineering. Our system is implemented in a web-based application server
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@inproceedings{Garden2003, author = {Matthew Garden and Gregory Dudek}, title = {On User Recommendations Based on Multiple Cues}, booktitle = {Proc. IEEE WI/IAT 2003 Workshop on Applications, Products and Services of Web-Based Support Systems (in conjunction with IEEE/WIC International Conference on Web Intelligence)}, year = {2003}, pages = {139--144}, address = {Halifax, NS}, isbn = {0-9734039-1-8} }
Path Planning Using Learned Constraints and Preferences
Simhon; Saul; Gregory Dudek

2003IEEE International Conference on Robotics and Automation
Abstract
Abstract
In this paper we present a novel method for robot path planning based on learning motion patterns. A motion pattern is defined as the path that results from applying a set of probabilistic constraints to a" raw" input path. For example, a user can sketch an approximate path for a robot without considered issues such as bounded radius of curvature and our system would then elaborate it to include such a constraint. In our approach, the constraints that generate a path are learned by capturing the statistical properties of a set of
Topics
path planning
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@inproceedings{simhon2003path, author = {Saul Simhon and Gregory Dudek}, title = {Path Planning Using Learned Constraints and Preferences}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2003}, address = {Taipei, Taiwan}, month = {May} }
Probabilistic Cooperative Localization and Mapping in Practice
Rekleitis; Ioannis; Sim; Robert; Milios; Evangelos; Gregory Dudek

2003IEEE International Conference on Robotics and Automation
Abstract
Abstract
In this paper we present a probabilistic framework for the reduction in the uncertainty of a moving robot pose during exploration by using a second robot to assist. A Monte Carlo Simulation technique (specifically, a Particle Filter) is employed in order to model and reduce the accumulated odometric error. Furthermore, we study the requirements to obtain an accurate yet timely pose estimate. A team of two robots is employed to explore an indoor environment in this paper, although several aspects of the approach have been extended to
Topics
cooperative localizationexploration strategieslocalizationslam
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@inproceedings{Rekleitis2003, author = {Ioannis Rekleitis and Robert Sim and Evangelos Milios and Gregory Dudek}, title = {Probabilistic Cooperative Localization and Mapping in Practice}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2003}, address = {Taipei, Taiwan}, month = {May} }
Range Synthesis for 3D Environment Modeling
Torres-Mendez; L.A.; Gregory Dudek

2003Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
In this paper a range synthesis algorithm is proposed as an initial solution to the problem of 3D environment modeling from sparse data. We develop a statistical learning method for inferring and extrapolating range data from as little as one intensity image and from those (sparse) regions where both range and intensity information is available. Our work is related to methods for texture synthesis using Markov Random Field methods. We demonstrate that MRF methods can also be applied to general intensity images with little associated range
Topics
3d reconstructionenvironment mappinglocalizationmarkov random fieldsslamunderwater robotics
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@inproceedings{Torres-Mendez2003, author = {Luz-Abril Torres-Mendez and Gregory Dudek}, title = {Range Synthesis for 3D Environment Modeling}, booktitle = {Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)}, address = {Las Vegas, NV}, month = {October}, year = {2003}, pages = {8} }
Range Synthesis for 3D Environment Modeling
Torres-Mendez; Luz-Abril; Gregory Dudek

2003Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
In this paper a range synthesis algorithm is proposed as an initial solution to the problem of 3D environment modeling from sparse data. We develop a statistical learning method for inferring and extrapolating range data from as little as one intensity image and from those (sparse) regions where both range and intensity information is available. Our work is related to methods for texture synthesis using Markov Random Field methods. We demonstrate that MRF methods can also be applied to general intensity images with little associated range
Topics
3d reconstructionenvironment mappinglocalizationmarkov random fieldsslamunderwater robotics
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@inproceedings{Torres-Mendez2003, author = {Luz-Abril Torres-Mendez and Gregory Dudek}, title = {Range Synthesis for 3D Environment Modeling}, booktitle = {Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)}, address = {Las Vegas, NV}, month = {October}, year = {2003}, pages = {8} }
RoboDaemon - A device-independent, network-oriented, modular mobile robot controller
Sim, Robert; Dudek, Gregory

2003IEEE International Conference on Robotics and Automation
Abstract
Abstract
We discuss a software environment for multi-robot, multi-platform mobile robot control and simulation. Like others, we have observed that mobile robotics research is greatly facilitated by the availability of a suitable simulator for both vehicle kinematics as well as sensing, and have created an environment that permits this while allowing a large measure of device independence. By using a multiprocessor internet-based architecture, our platform permits multiple users to use a variety of programming interfaces (visual, script-based or various
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@inproceedings{sim2003robodaemon, title={RoboDaemon - A device-independent, network-oriented, modular mobile robot controller}, author={Sim, Robert and Dudek, Gregory}, booktitle={IEEE International Conference on Robotics and Automation}, year={2003}, address={Taipei, Taiwan}, month={May} }
Automated Enhancement of 3-D Models
Torres-Mendez; L.A.; Gregory Dudek

2002Proc. Eurographics 2002 (Geometric and Physics Based Modeling)
Abstract
Abstract
The acquisition of a 3D model of a real environment can be accomplished using range sensors. In practice, suitable sensors to densely cover a large environment are often impractical. This paper presents ongoing work on the synthesis of 3D environment models from as little as one intensity image and sparse range data. Our method is based on interpolating the available range data using statistical inferences learned from the available intensity image and from those (sparse) regions where both range and intensity information
Topics
3d reconstructionenvironment mappinglocalizationslam
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@inproceedings{Torres-Mendez2002, author = {L. A. Torres-Mendez and Gregory Dudek}, title = {Automated Enhancement of 3-D Models}, booktitle = {Proc. Eurographics 2002 (Geometric and Physics Based Modeling)}, address = {Saarbrucken, Germany}, month = {September}, year = {2002} }

Automated Parameter Estimation for Procedural Texturing

Bourque; Eric; Gregory Dudek

2002Proc. 13th Eurographics Workshop on Rendering

Abstract

Topics

computer graphicsimage matchingtexture

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@inproceedings{bourque2002automated,
  title={Automated Parameter Estimation for Procedural Texturing},
  author={Bourque, Eric and Dudek, Gregory},
  booktitle={Proc. 13th Eurographics Workshop on Rendering},
  year={2002},
  location={Pisa, Italy}
}

Multi-Robot Cooperative Localization: A Study of Trade-offs Between Efficiency and Accuracy
Rekleitis; Ioannis; Sim; Robert; Milios; Evangelos; Gregory Dudek

2002Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems
Abstract
Abstract
This paper examines the tradeoffs between different classes of sensing strategy and motion control strategy in the context of terrain mapping with multiple robots. We consider a larger group of robots that can mutually estimate one another's position (in 2D or 3D) and uncertainty using a sample-based (particle filter) model of uncertainty. Our prior work has dealt with a pair of robots that estimate one another's position using visual tracking and coordinated motion. Here we extend these results and consider a richer set of sensing and
Topics
cooperative localization
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@inproceedings{Rekleitis2002, author = {Ioannis Rekleitis and Robert Sim and Evangelos Milios and Gregory Dudek}, title = {Multi-Robot Cooperative Localization: A Study of Trade-offs Between Efficiency and Accuracy}, booktitle = {Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems}, year = {2002}, pages = {2690--2695}, address = {Lausanne, Switzerland} }
On the Positional Uncertainty of Multi-Robot Cooperative Localization
Rekleitis; Ioannis; Sim; Robert; Milios; Evangelos; Gregory Dudek

2002Proc. Naval Research Labs/NATO Workshop on Multi-Robot Systems
Abstract
Abstract
This paper deals with terrain mapping and position estimation using multiple robots. Here we will discuss work where a larger group of robots can mutually estimate one another's position (in 2D or 3D) and uncertainty using a sample-based (particle filter) model of uncertainty. Our prior work has dealt with a pair of robots that estimate one another's position using visual tracking and coordinated motion and we extend these results and consider a richer set of sensing and motion options. In particular, we focus on issues related to
Topics
cooperative localization
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@inproceedings{Rekleitis2002, author = {Ioannis Rekleitis and Robert Sim and Evangelos Milios and Gregory Dudek}, title = {On the Positional Uncertainty of Multi-Robot Cooperative Localization}, booktitle = {Proc. Naval Research Labs/NATO Workshop on Multi-Robot Systems}, year = {2002}, address = {Washington, DC}, note = {to appear} }
Collaborative Exploration for Map Construction
Rekleitis; Ioannis; Sim; Robert; Milios; Evangelos; Gregory Dudek

2001Proc. International Symposium on Computational Intelligence in Robotics and Automation (CIRA)
Abstract
Abstract
We consider the problem of map learning while maintaining ground-truth pose estimates. Map learning is important in tasks that require a model of the environment or some of its features. As a robot collects data, uncertainty about its position accumulates and corrupts its knowledge of the positions from which observations are taken. We address this problem by employing cooperative localization; that is, deploying a second robot to observe the other as it explores, thereby establishing a virtual tether, and enabling an accurate estimate of the
Topics
cooperative localizationexploration strategieslocalizationslam
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@inproceedings{Rekleitis2001, author = {Ioannis Rekleitis and Robert Sim and Evangelos Milios and Gregory Dudek}, title = {Collaborative Exploration for Map Construction}, booktitle = {Proc. International Symposium on Computational Intelligence in Robotics and Automation (CIRA)}, year = {2001}, location = {Banff, Canada}, pages = {6} }
Collaborative Exploration for the Construction of Visual Maps
Rekleitis; Ioannis; Sim; Robert; Milios; Evangelos; Gregory Dudek

2001Proceedings of IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We examine the problem of learning a visual map of the environment while maintaining an accurate pose estimate. Our approach is based on using two robots in a simple collaborative scheme. Without outside information, as a robot collects training images, its position estimate accumulates errors, thus corrupting its knowledge of the positions from which observations are taken. We address this problem by deploying a second robot to observe the first one as it explores, thereby establishing a virtual tether, and enabling an accurate
Topics
complexity boundscooperative localizationlocalizationslamteleoperation
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@inproceedings{Rekleitis2001, author = {Ioannis Rekleitis and Robert Sim and Evangelos Milios and Gregory Dudek}, title = {Collaborative Exploration for the Construction of Visual Maps}, booktitle = {Proceedings of IEEE/RSJ Conference on Intelligent Robots and Systems (IROS)}, year = {2001}, location = {Hawaii}, pages = {6} }
Collaborative Robot Exploration and Rendezvous: Algorithms, Performance Bounds and Observations
Roy; N.; Gregory Dudek

2001Autonomous Robots
Abstract
Abstract
We consider the problem of how two heterogeneous robots can arrange to meet in an unknown environment from unknown starting locations: that is, the problem of arranging a robot rendezvous. We are interested, in particular, in allowing two robots to rendezvous so that they can collaboratively explore an unknown environment. Specifically, we address the problem of how a pair of exploring agents that cannot communicate with one another over long distances can meet if they start exploring at different unknown locations in an unknown
Topics
landmark-based methodsrendezvous
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@article{roy2001collaborative, title={Collaborative Robot Exploration and Rendezvous: Algorithms, Performance Bounds and Observations}, author={Roy, Nicholas and Dudek, Gregory}, journal={Autonomous Robots}, volume={11}, number={2}, pages={117--136}, year={2001} }
Image-Driven Procedural Texture Specification
Bourque; Eric; Gregory Dudek

2001Proc. Vision Interface
Abstract
Abstract
In this paper we describe an approach to the automated specification of procedural textures to be used in rendering, based on representative samples. Procedural textures exhibit many advantages over traditional surface texturing techniques, but unfortunately finding the correct procedural texture and appropriate parameters to create the desired texture can be a daunting task for even the most experienced computer graphics artists. The method we propose here, which we refer to as image-based procedural texturing, allows the
Topics
computer graphicstexture
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@inproceedings{bourque2001image, author = {Eric Bourque and Gregory Dudek}, title = {Image-Driven Procedural Texture Specification}, booktitle = {Proc. Vision Interface}, year = {2001}, pages = {1--6}, address = {Ottawa, Canada}, month = {June} }
Learning Generative Models of Scene Features
Sim; Robert; Gregory Dudek

2001Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Abstract
Abstract
We present a method for learning a set of generative models which are suitable for representing selected image-domain features of a scene as a function of changes in the camera viewpoint. Such models are important for robotic tasks, such as probabilistic position estimation (ie localization), as well as visualization. Our approach entails the automatic selection of the features, as well as the synthesis of models of their visual behavior. The model we propose is capable of generating maximum-likelihood views, as well as a
Topics
bayesian inferencegenerative ailocalizationobject recognition
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@inproceedings{sim2001learning, title={Learning Generative Models of Scene Features}, author={Sim, Robert and Dudek, Gregory}, booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2001}, pages={7}, address={Hawaii} }
Learning Generative Models of Scene Features
Sim; Robert; Gregory Dudek

2001Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Abstract
Abstract
We present a method for learning a set of generative models which are suitable for representing selected image-domain features of a scene as a function of changes in the camera viewpoint. Such models are important for robotic tasks, such as probabilistic position estimation (ie localization), as well as visualization. Our approach entails the automatic selection of the features, as well as the synthesis of models of their visual behavior. The model we propose is capable of generating maximum-likelihood views, as well as a
Topics
bayesian inferencegenerative ailocalizationobject recognition
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@inproceedings{sim2001learning, title={Learning Generative Models of Scene Features}, author={Sim, Robert and Dudek, Gregory}, booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2001}, pages={7}, address={Hawaii} }
On the Elaboration of Hand-Drawn Sketches
Simhon; S.; Gregory Dudek

2001Active Media Technology
Abstract
Abstract
This work considers an approach for artificially enhancing the richness and level of detail of graphical scenes. In particular, we examine a method for automatically generating high-resolution novel curves from manually sketched drawings of those curves. The essential idea is to augment the hand-drawn curves using prior knowledge to produce a more elaborated picture. Our method uses multi-scale analysis of a class of training data to capture statistical properties of the set. These properties are then conditioned at a coarse
Topics
complexity boundscomputer graphicsgenerative aiknowledge distillationtexturewavelet analysis
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@inproceedings{Simhon2001, author = {Simhon, S. and Gregory Dudek}, title = {On the Elaboration of Hand-Drawn Sketches}, booktitle = {Active Media Technology}, year = {2001}, address = {Hong Kong}, month = {Dec} }

Computational Principles of Mobile Robotics (first edition)

Dudek, Gregory; Jenkin, Michael

2000Cambridge University Press

Abstract

Computational Principles of Mobile Robotics (first edition)

Topics

localizationslam

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@book{dudek2000computational,
  title={Computational Principles of Mobile Robotics (first edition)},
  author={Dudek, Gregory and Jenkin, Michael},
  edition={1st},
  year={2000},
  publisher={Cambridge University Press},
  isbn={9780521692120},
  pages={450}
}

Evaluation of Computation Attention Operators using Human Image Recognition
Sandra Polifroni; Frank Ferrie; Gregory Dudek

2000Investigative Opthalmology and Visual Science (Suppl)
Abstract
Abstract
This thesis presents a novel method of evaluating computationaI attention operators, which select locations of interest in an image, using a human image recognition task. Assuming that locations which are maximally interesting will be most useful for recognizing an image, it follows that a location selected by an attention operator will facilitate image recognition if it is of interest to a human. Since attention operators are increasingly being used to replace humans in vision tasks, it is relevant that their performance be compared to human vision
Topics
human-robot interactionvisual agnosia
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@article{Polifroni2000, author = {Sandra Polifroni and Frank Ferrie and Gregory Dudek}, title = {Evaluation of Computation Attention Operators using Human Image Recognition}, journal = {Investigative Opthalmology and Visual Science (Suppl)}, year = {2000}, month = {May}, pages = {196--197}, publisher = {The Association for Research in Vision and Opthalmology} }
Graph-Based Exploration using Multiple Robots
Rekleitis; Ioannis; Milios; Evangelos; Gregory Dudek

2000Proc. 5th International Symposium on Distributed Autonomous Robotic Systems (DARS)
Abstract
Abstract
We present an approach to multi-robot exploration of large environments. Our method is designed to be robust in the face of arbitrarily large odometry errors or objects with poor reflectance characteristics. The algorithm achieves its robustness by using a team of cooperating agents. The critical aspect of our method is the use of a vision system that sweeps areas of free space and generates a graph-based description of the environment. This graph is used to guide the exploration process and can also be used for subsequent
Topics
complexity boundscooperative localizationenvironment mappingexploration strategieslocalizationslam
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@inproceedings{Rekleitis2000, author = {Ioannis Rekleitis and Evangelos Milios and Gregory Dudek}, title = {Graph-Based Exploration using Multiple Robots}, booktitle = {Proc. 5th International Symposium on Distributed Autonomous Robotic Systems (DARS)}, year = {2000}, pages = {241--250}, address = {Knoxville, USA}, month = {October} }
Local Appearance for Robust Object Recognition
Jugessur; Deeptiman; Gregory Dudek

2000Proc. IEEE Computer Vision and Pattern Recognition
Abstract
Abstract
We present an approach to appearance-based object recognition using single camera images. Our approach is based on using an attention mechanism to obtain visual features that are generic, robust and informative. The features themselves are recognized using principal components an the frequency domain. In this paper we show how the visual characteristics of only a small number of such features can be used for appearance-based object recognition that is not confounded by planar rotations or background clutter.
Topics
object recognition
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@inproceedings{jugessur2000local, title={Local Appearance for Robust Object Recognition}, author={Jugessur, Deeptiman and Dudek, Gregory}, booktitle={Proc. IEEE Computer Vision and Pattern Recognition}, year={2000}, month={June} }
Multi-Robot Collaboration for Robust Exploration
Rekleitis; Ioannis; Gregory Dudek

2000Proc. of IEEE International Conference in Robotics and Automation
Abstract
Abstract
This paper presents a new sensing modality for multirobot exploration. The approach is based on using a pair of robots that observe each other, and act in concert to reduce odometry errors. We assume the robots can both directly sense nearby obstacles and see each other. The proposed approach improves the quality of the map by reducing the inaccuracies that occur over time from dead reckoning errors. Furthermore, by exploiting the ability of the robots to see each other, we can detect opaque obstacles in the environment
Topics
complexity boundscooperative localizationexploration strategieslandmark-based methodslocalizationpath planningreinforcement learningslamunderwater robotics
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@inproceedings{Rekleitis2000, author = {Ioannis Rekleitis and Gregory Dudek}, title = {Multi-Robot Collaboration for Robust Exploration}, booktitle = {Proc. of IEEE International Conference in Robotics and Automation}, year = {2000}, pages = {3164--3169}, address = {San Francisco, CA}, month = apr, }
Multi-Robot Collaboration for Robust Exploration
Rekleitis; Ioannis; Milios; Evangelos; Gregory Dudek

2000Proc. of IEEE International Conference in Robotics and Automation
Abstract
Abstract
This paper presents a new sensing modality for multirobot exploration. The approach is based on using a pair of robots that observe each other, and act in concert to reduce odometry errors. We assume the robots can both directly sense nearby obstacles and see each other. The proposed approach improves the quality of the map by reducing the inaccuracies that occur over time from dead reckoning errors. Furthermore, by exploiting the ability of the robots to see each other, we can detect opaque obstacles in the environment
Topics
complexity boundscooperative localizationexploration strategieslandmark-based methodslocalizationpath planningreinforcement learningslamunderwater robotics
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@inproceedings{Rekleitis2000, author = {Ioannis Rekleitis and Gregory Dudek}, title = {Multi-Robot Collaboration for Robust Exploration}, booktitle = {Proc. of IEEE International Conference in Robotics and Automation}, year = {2000}, pages = {3164--3169}, address = {San Francisco, CA}, month = apr, }
On the Automated Construction of Image-Based Maps
Bourque; Eric; Gregory Dudek

2000Autonomous Robots
Abstract
Abstract
For many tasks, we wish to record or recover the description of a remote environment so that it can be inspected by a person. This is the problem we address in this paper. Rather than recovering a geometric description of an environment, as many robotics systems attempt to do, we seek to recover a model of an environment in terms of its appearance from a set of carefully selected viewpoints. Our hope is that this type of model is both more accessible to humans for many realistic tasks, and also more readily achieved with automated systems
Topics
complexity boundsenvironment mappinggenerative aigraph theorylocalizationslamunderwater robotics
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@article{bourque2000automated, title={On the Automated Construction of Image-Based Maps}, author={Bourque, Eric and Dudek, Gregory}, journal={Autonomous Robots}, volume={8}, number={2}, pages={103--104}, year={2000}, month={April} }
On-line Construction of Iconic Maps
Bourque; Eric; Gregory Dudek

2000Proc. of IEEE International Conference in Robotics and Automation
Abstract
Abstract
This paper describes an approach to the automated creation of virtual realities (or virtual maps) of an a priori unknown environment by using a mobile robot. The method we propose is aimed at the creation of an image-based or iconic map, rather than a representation in terms of 2D or 3D spatial occupancy. A key aspect of this is having a mobile robot automatically select points and views of interest that can be used to exemplify the appearance of the environment. This paper develops the use of alpha-backtracking as a
Topics
complexity boundsenvironment mappinggenerative aigraph theorylocalizationslam
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@inproceedings{bourque2000online, author = {Eric Bourque and Gregory Dudek}, title = {On-line Construction of Iconic Maps}, booktitle = {Proc. of IEEE International Conference in Robotics and Automation}, year = {2000}, address = {San Francisco, CA}, month = {April} }
Robust Place Recognition using Local Appearance-Based Methods
Jugessur; Deeptiman; Gregory Dudek

2000Proc. of IEEE International Conference in Robotics and Automation
Abstract
Abstract
We present an approach to the automatic recognition of locations or landmarks using single camera images. Our approach is to learn visual features in the appearance domain that can be used to characterize an object or a location. These features are defined statistically and then are recognized using principal components in the frequency domain. We show that this technique can be used to recognize specific objects on varying backgrounds, as well as environmental features.
Topics
landmark-based methodslocalizationobject recognitionplace recognitionslam
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@inproceedings{jugessur2000robust, title={Robust Place Recognition using Local Appearance-Based Methods}, author={Jugessur, Deeptiman and Dudek, Gregory}, booktitle={Proc. of IEEE International Conference in Robotics and Automation}, year={2000}, month={April}, address={San Francisco, CA} }

Stochastic Reconstruction from Coarse Data

Simhon; Saul; Gregory Dudek

2000Proc. Graphics Interface

Abstract

Stochastic Reconstruction from Coarse Data

Topics

complexity boundsknowledge distillation

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@inproceedings{simhon2000stochastic,
  author    = {Saul Simhon and Gregory Dudek},
  title     = {Stochastic Reconstruction from Coarse Data},
  booktitle = {Proc. Graphics Interface},
  year      = {2000},
  address   = {Montreal},
  month     = {May},
  pages     = {120--126}
}

The Paparazzi Problem
Jenkin; Michael; Gregory Dudek

2000Proc. IEEE/RSJ IROS 2000
Abstract
Abstract
Multiple mobile robots, or robot collectives, have been proposed as solutions to various tasks in which distributed sensing and action are required. Here we consider applying a collective of robots to the paparazzi problem-the problem of providing sensor coverage of a target robot. We demonstrate how the computational task of the collective can be formulated as a global energy minimization task over the entire collective, and show how individual members of the collective can solve the task in a distributed fashion so that the entire
Topics
cooperative localization
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@inproceedings{jenkin2000paparazzi, author = {Michael Jenkin and Gregory Dudek}, title = {The Paparazzi Problem}, booktitle = {Proc. IEEE/RSJ IROS 2000}, year = {2000}, address = {Takamatsu, Japan} }
Efficient Topological Exploration
Rekleitis; Ioannis; Dujmovi\'c; Vida; Gregory Dudek

1999Proc. of IEEE International Conference in Robotics and Automation
Abstract
Abstract
We consider the robot exploration of a planar graph-like world. The robot's goal is to build a complete map of its environment. The environment is modeled as an arbitrary undirected planar graph which is initially unknown to the robot. The robot cannot distinguish vertices and edges that it has explored from the unexplored ones. The robot is assumed to be able to autonomously traverse graph edges, recognize when it has reached a vertex, and enumerate edges incident upon the current vertex. The robot cannot measure distances nor
Topics
complexity boundsexploration strategiesgraph theorylocalizationslamunderwater robotics
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@inproceedings{Rekleitis1999, author = {Ioannis Rekleitis and Vida Dujmovi\'c and Gregory Dudek}, title = {Efficient Topological Exploration}, booktitle = {Proc. of IEEE International Conference in Robotics and Automation}, year = {1999}, pages = {676--681}, address = {Detroit, MI}, month = {May} }

Image Mosaicking Using Zernike Moments

Badra; F.; Qumsieh; Q.; Gregory Dudek

1999International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)

Abstract

Image Mosaicking Using Zernike Moments

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@article{Badra1999,
  author    = {F. Badra and Q. Qumsieh and Gregory Dudek},
  title     = {Image Mosaicking Using Zernike Moments},
  journal   = {International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)},
  volume    = {13},
  number    = {4},
  pages     = {685--704},
  month     = {August},
  year      = {1999}
}

Learning and Evaluating Visual Features for Pose Estimation
Sim; Robert; Gregory Dudek

1999Proceedings of the International Conference on Computer Vision
Abstract
Abstract
We present a method for learning a set of visual landmarks which are useful for pose estimation. The landmark learning mechanism is designed to be applicable to a wide range of environments, and generalized for different approaches to computing a pose estimate. Initially, each landmark is detected as a focal extremum of a measure of distinctiveness and represented by a principal components encoding which is exploited for matching. Attributes of the observed landmarks can be parameterized using a generic parameterization method
Topics
exploration strategies
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@inproceedings{sim1999learning, author = {Robert Sim and Gregory Dudek}, title = {Learning and Evaluating Visual Features for Pose Estimation}, booktitle = {Proceedings of the International Conference on Computer Vision}, year = {1999}, pages = {32--40}, address = {Kerkyra (Corfu), Greece}, month = sep }
Learning Environmental Features for Position Estimation
Robert Sim; Gregory Dudek

1999Proc. of the IEEE Workshop on Perception for Mobile Agents
Abstract
Abstract
We present a method for learning a set of environmental features which are useful for pose estimation. The landmark learning mechanism is designed to be applicable to a wide range of environments, and generalized for different sensing modalities. In the context of computer vision, each landmark is detected as a local extremum of a measure of distinctiveness and represented by an appearance-based encoding which is exploited for matching. The set of obtained landmarks can be parameterized and then evaluated in terms of their utility for the
Topics
landmark-based methodslocalization
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@inproceedings{sim1999learning, author = {Robert Sim and Gregory Dudek}, title = {Learning Environmental Features for Position Estimation}, booktitle = {Proc. of the IEEE Workshop on Perception for Mobile Agents}, year = {1999}, pages = {7--14}, address = {Fort Collins, Colorado}, month = {June} }
Learning Environmental Features for Position Estimation
Sim; Robert; Gregory Dudek

1999Proc. of the IEEE Workshop on Perception for Mobile Agents
Abstract
Abstract
We present a method for learning a set of environmental features which are useful for pose estimation. The landmark learning mechanism is designed to be applicable to a wide range of environments, and generalized for different sensing modalities. In the context of computer vision, each landmark is detected as a local extremum of a measure of distinctiveness and represented by an appearance-based encoding which is exploited for matching. The set of obtained landmarks can be parameterized and then evaluated in terms of their utility for the
Topics
landmark-based methodslocalization
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@inproceedings{sim1999learning, author = {Robert Sim and Gregory Dudek}, title = {Learning Environmental Features for Position Estimation}, booktitle = {Proc. of the IEEE Workshop on Perception for Mobile Agents}, year = {1999}, pages = {7--14}, address = {Fort Collins, Colorado}, month = {June} }
Learning Visual Landmarks for Pose Estimation
Sim; Robert; Gregory Dudek

1999Canadian Artificial Intelligence
Abstract
Abstract
We present an approach to vision-based mobile robot localization, even without an a-priori pose estimate. This is accomplished by learning a set of visual features called image-domain landmarks. The landmark learning mechanism is designed to be applicable to a wide range of environments. Each landmark is detected as a focal extremum of a measure of uniqueness and represented by an appearance-based encoding. Localization is performed using a method that matches observed landmarks to learned prototypes and generates
Topics
environment mapping
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@article{sim1999learning, title={Learning Visual Landmarks for Pose Estimation}, author={Sim, Robert and Dudek, Gregory}, journal={Canadian Artificial Intelligence}, volume={43}, year={1999}, pages={13--17} }
Learning Visual Landmarks for Pose Estimation (journal version)
Sim; Robert; Gregory Dudek

1999Canadian Artificial Intelligence
Abstract
Abstract
Learning Visual Landmarks for Pose Estimation (journal version)
Topics
deep learninglocalizationslam
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@article{sim1999learning, title={Learning Visual Landmarks for Pose Estimation (journal version)}, author={Sim, Robert and Dudek, Gregory}, journal={Canadian Artificial Intelligence}, volume={43}, year={1999}, pages={13--17} }
A global topological map formed by local metric maps
Simhon; Saul; Gregory Dudek;

1998Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We describe a method of mapping large scale static environments using a hybrid topological-metric model. A global map is formed from a set of local maps organized in a topological structure. Each local map contains quantitative environment information using a local reference frame. They are denoted as islands of reliability because they provide accurate metric information of the environment. The mapping problem then becomes where to place the islands of reliability and to what extent should they cover the environment. This is
Topics
complexity boundsgraph theorylocalizationslam
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@inproceedings{simhon1998global, author = {Saul Simhon and Gregory Dudek}, title = {A global topological map formed by local metric maps}, booktitle = {Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)}, year = {1998}, pages = {1708--1714}, address = {Victoria, BC}, month = {October} }

A semantic proximity effect on object recognition in visual agnosia for biological kinds

Lecours; S.; Caille; S.; Fontaine; S.; Arguin; M.; Bub; D.; Gregory Dudek

1998BRAIN AND COGNITION

Abstract

Topics

object recognitionvisual agnosia

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@article{lecours1998semantic,
 abstract = {},
 author = {Lecours, S and Arguin, M and Bub, D and Dudek, G and Caille, S and Fontaine, S},
 journal = {BRAIN AND COGNITION},
 number = {1},
 pages = {138--141},
 pub_year = {1998},
 publisher = {ACADEMIC PRESS INC 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA},
 title = {A semantic proximity effect on object recognition in visual agnosia for biological kinds},
 venue = {… COGNITION},
 volume = {37}
}

Automated Image-Based Mapping
Bourque; Eric; Gregory Dudek;

1998Proc. IEEE Workshop on Perception for Mobile Agents
Abstract
Abstract
We describe an approach to the automated construction of visual maps of an unknown environment. These maps take the form of image-based “walk-throughs” rather than 2D or 3D models. Our approach is based on the selection of informative viewpoints within the environment. These viewpoints are locations in the environment associated with views containing maximal visual interest. This approach to environment representation is analogous to image compression. Our goal is to obtain a set of representative views
Topics
computer graphicsenvironment mappingimage matchinglocalizationslam
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@inproceedings{bourque1998automated, author = {Eric Bourque and Gregory Dudek}, title = {Automated Image-Based Mapping}, booktitle = {Proc. IEEE Workshop on Perception for Mobile Agents}, year = {1998}, pages = {61--70}, address = {Santa Barbara, CA}, month = jun }

Localizing a robot with minimum travel

Romanik; Kathleen; Whitesides; Sue; Gregory Dudek

1998SIAM Journal on Computing

Abstract

We consider the problem of localizing a robot in a known environment modeled by a simple polygon P. We assume that the robot has a map of P but is placed at an unknown location inside P. From its initial location, the robot sees a set of points called the visibility polygon V of its location. In general, sensing at a single point will not suffice to uniquely localize the robot, since the set H of points in P with visibility polygon V may have more than one element. Hence, the robot must move around and use range sensing and a compass to

Topics

complexity boundslocalizationslam

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@article{dudek1998localizing,
 abstract = {We consider the problem of localizing a robot in a known environment modeled by a simple polygon P. We assume that the robot has a map of P but is placed at an unknown location inside P. From its initial location, the robot sees a set of points called the visibility polygon V of its location. In general, sensing at a single point will not suffice to uniquely localize the robot, since the set H of points in P with visibility polygon V may have more than one element. Hence, the robot must move around and use range sensing and a compass to},
 author = {Dudek, Gregory and Romanik, Kathleen and Whitesides, Sue},
 journal = {SIAM Journal on Computing},
 number = {2},
 pages = {583--604},
 pub_year = {1998},
 publisher = {SIAM},
 title = {Localizing a robot with minimum travel},
 venue = {SIAM Journal on Computing},
 volume = {27}
}

Mobile robot localization from learned landmarks
Sim; Robert; Gregory Dudek;

1998Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Presents an approach to vision-based mobile robot localization. In an attempt to capitalize on the benefits of both image and landmark-based methods, we describe a method that combines their strengths. Images are encoded as a set of visual features called landmarks. Potential landmarks are detected using an attention mechanism implemented as a measure of uniqueness. They are then selected and represented by an appearance-based encoding. Localization is performed using a landmark tracking and interpolation method which obtains
Topics
landmark-based methodsobject recognition
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@inproceedings{sim1998mobile, author = {Robert Sim and Gregory Dudek}, title = {Mobile robot localization from learned landmarks}, booktitle = {Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)}, year = {1998}, pages = {1060--1065}, address = {Victoria, BC}, month = {October} }
On 3-D surface reconstruction using shape from shadows
Daum; Michael; Gregory Dudek

1998Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231)
Abstract
Abstract
In this paper we discuss new results on the Shape From Darkness problem: using the motion of cast shadows to recover scene structure. Our approach is based on collecting a set of images from a fixed viewpoint as a known light source mover;" across the sky". Previously published solutions to this problem have performed the reconstruction only for cross sections of the scene. In this paper, we present a reconstruction algorithm and discuss the reconstruction of an entire 3-D scene under various light source trajectories. We also
Topics
3d reconstruction
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@inproceedings{Daum1998, author = {M. Daum and G. Dudek}, title = {On 3-D surface reconstruction using shape from shadows}, booktitle = {Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231)}, year = {1998}, pages = {461--468}, doi = {10/b8wprs}, month = jun }
On Multiagent Exploration
Rekleitis; Ioannis; Milios; Evangelos; Gregory Dudek;

1998Proc. Vision Interface
Abstract
Abstract
This paper describes a technique for multi-agent exploration of an unknown environment, that improves the quality of the map by reducing the inaccuracies that occur over time from dead reckoning errors. We present an algorithmic solution, simulation results, as well as a cost analysis and experimental data. The approach is based on using a pair of robots that observe one another's behaviour, thus greatly reducing odometry errors. We assume the robots can both directly sense nearby obstacles and see one another. We have
Topics
complexity boundscooperative localizationexploration strategieslocalizationslam
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@inproceedings{Rekleitis1998, author = {Ioannis Rekleitis and Evangelos Milios and Gregory Dudek}, title = {On Multiagent Exploration}, booktitle = {Proc. Vision Interface}, year = {1998}, pages = {455--461}, address = {Vancouver, BC}, month = {June} }
On the Integration of Mobile Robot Systems
Dudek; Gregory

1998AAAI Spring Symposium
Abstract
Abstract
On the Integration of Mobile Robot Systems
Topics
complexity boundscooperative localizationlocalizationrobotic collectivesslamtelecommunications
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@inproceedings{dudek1998integration, author = {Gregory Dudek}, title = {On the Integration of Mobile Robot Systems}, booktitle = {AAAI Spring Symposium}, year = {1998}, pages = {20--27}, address = {Stanford, CA} }
Out of the Dark: Using Shadows to Reconstruct 3D Surfaces
Daum; Michael; Gregory Dudek

1998Proc. Asian Conference on Computer Vision
Abstract
Abstract
Shape From Darkness refers to using the shadows cast by a scene to reconstruct the structure of the scene. A collection of images associated with different light source positions is used. Previously published solutions to this problem have performed the reconstruction only for cross sections of the scene. We propose a variant of Shape From Darkness which is capable of reconstructing the entire 3-D scene. In addition, this algorithm can be applied to a broader class of light source trajectories, including trajectories which
Topics
3d reconstructioncomplexity boundsobject recognition
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@inproceedings{daum1998out, title={Out of the Dark: Using Shadows to Reconstruct 3D Surfaces}, author={Daum, Michael and Dudek, Gregory}, booktitle={Proc. Asian Conference on Computer Vision}, pages={72--79}, year={1998}, address={Hong Kong, China}, month={January}, series={Lecture Notes in Computer Science}, volume={1351}, editor={Goos, G. and Hartmanis, J. and van Leeuwen, J.}, publisher={Springer} }
Profile of a Winner: McGill University
Dudek; G.

1998American Association for Artificial Intelligence Magazine
Abstract
Abstract
Much of the work at the McGill Mobile Robotics Lab concerns computational problems related to use of sensors: vision, laser, and sonar. As a result, the McGill team entered the nonmanipulator category. The team was made up of four students: Francois Belair, Eric Bourque, Deeptiman Jugessur, and Robert Sim, with myself acting as faculty mentor. The robot they used was a NOMAD 200, a chest-height cylindrical robot with a three-wheeled synchrodrive, a standard ring of 16 sonar sensors, and a single-color camera mounted on a
Topics
sonar and acoustics
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@article{dudek1998profile, author = {Dudek, G.}, title = {Profile of a Winner: McGill University}, journal = {American Association for Artificial Intelligence Magazine}, year = {1998}, month = {Summer}, note = {(part of an article of the AAAI-97 mobile robotics competition)} }
Robotic Sightseeing - A Method for Automatically Creating Virtual Environments
Eric Bourque; Philippe Ciaravola; Gregory Dudek

1998Proc. IEEE International Conference on Robotics and Automation
Abstract
Abstract
This paper describes the fully automatic creation of an environment's description using an image-based representation. This representation is a collection of cylindrical sample images combined into an" image-based virtual reality". The locations at which the environment will be sampled are chosen automatically using an operator inspired by models of human visual attention and saccadic motion. The image acquisition is performed by a mobile robot. The selection of vantage points is based on an analysis of the edge structure of sampled
Topics
computer graphicsenvironment mappinghuman-robot interactionimage matchinglocalizationslam
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@inproceedings{bourque1998robotic, author = {Eric Bourque and Philippe Ciaravola and Gregory Dudek}, title = {Robotic Sightseeing - A Method for Automatically Creating Virtual Environments}, booktitle = {Proc. IEEE International Conference on Robotics and Automation}, year = {1998}, pages = {3186--3191}, publisher = {IEEE Press}, address = {Leuven, Belgium}, month = {May} }

Robotics and Empiricism

Dudek; Gregory

1998AAAI Spring Symposium (position paper)

Abstract

Robotics and Empiricism

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@inproceedings{dudek1998robotics,
  author    = {Gregory Dudek},
  title     = {Robotics and Empiricism},
  booktitle = {AAAI Spring Symposium (position paper)},
  year      = {1998},
  pages     = {97--98},
  address   = {Stanford, CA}
}

Robust Mosaicing Using Zernike Moments
Badra; Fady; Qumsieh; Ala; Gregory Dudek

1998Proc. Vision Interface
Abstract
Abstract
This paper presents an approach to the registration of individual images to one another to produce a larger composite mosaic. The approach is based on the use of the moments of Zernike orthogonal polynomials to compute the relative scale, rotation and translation between the images. A preliminary stage involves the use of an attention-like operation to estimate potential approximate correspondence points between the images based on extrema of local edge element density. Experimental results illustrate that the technique is
Topics
localizationslam
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@inproceedings{badra1998robust, title={Robust Mosaicing Using Zernike Moments}, author={Badra, Fady and Qumsieh, Ala and Dudek, Gregory}, booktitle={Proc. Vision Interface}, pages={149--156}, year={1998}, address={Vancouver, BC}, month={June} }
Selecting Targets for Local Reference Frames
Simhon; Saul; Gregory Dudek

1998Proc. IEEE International Conference on Robotics and Automation
Abstract
Abstract
Addresses the problem of seeking out parts of the environment that provide adequate features in order to perform robot localization. The objective is to choose good regions in which local metric maps can be established. A distinctiveness measure is defined as a measure of how well the environment allows the robot to accomplish a task, in our case the task being localization. The distinctiveness measure is evaluated as a function of both the localization strategy and the environment. Areas in the environment are considered to have
Topics
complexity boundsenvironment mappinglandmark-based methodslocalizationslam
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@inproceedings{simhon1998selecting, title={Selecting Targets for Local Reference Frames}, author={Simhon, Saul and Dudek, Gregory}, booktitle={Proc. IEEE International Conference on Robotics and Automation}, pages={2840--2845}, year={1998}, organization={IEEE}, address={Leuven, Belgium}, publisher={IEEE Press} }

Topological Exploration of Unknown Environments with Multiple Robots

Jenkin; Michael; Milios; Evangelos; Gregory Dudek

1998Proc. of the World Automation Congress (WAC '98), Anchorage, Alaska, May 1998, (8 pages: proceedings on CD-ROM). ( Also appears inRobotic and Manufacturing Systems - Recent Results in Research, Development and Applications, M. Jamshidi, F. Pierrot and M. Kamel (eds.), Volume 7, TSI Press, Albuquerque, NM, USA, 1998.)

Abstract

Topological Exploration of Unknown Environments with Multiple Robots

Topics

complexity boundsexploration strategiesgraph theorylocalizationslamunderwater robotics

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@inproceedings{Jenkin1998,
  author    = {Michael Jenkin and Evangelos Milios and Gregory Dudek},
  title     = {Topological Exploration of Unknown Environments with Multiple Robots},
  booktitle = {Proc. of the World Automation Congress (WAC '98)},
  address   = {Anchorage, Alaska},
  month     = {May},
  year      = {1998},
  note      = {(8 pages: proceedings on CD-ROM)}
}

@incollection{Jenkin1998a,
  author    = {Michael Jenkin and Evangelos Milios and Gregory Dudek},
  title     = {Topological Exploration of Unknown Environments with Multiple Robots},
  booktitle = {Robotic and Manufacturing Systems - Recent Results in Research, Development and Applications},
  editor    = {M. Jamshidi and F. Pierrot and M. Kamel},
  volume    = {7},
  publisher = {TSI Press},
  address   = {Albuquerque, NM, USA},
  year      = {1998}
}

Viewpoint Selection -- An Autonomous Robotic System for Virtual Environment Creation
Bourque, Eric; Dudek, Gregory

1998Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Describes an integrated system for the automatic construction of image-based virtual realities to describe a real environment. A mobile robot autonomously navigates through the environment and uses a camera to make observations. At locations that are deemed sufficiently interesting, panoramic images are collected that are used to construct a multi-node VR movie. Images of the environment are classified in terms of two features related to human attention: edge element density and edge orientation. The system deems locations
Topics
complexity boundsenvironment mappinggraph theoryhuman-robot interactionlocalizationslam
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@inproceedings{bourque1998viewpoint, title={Viewpoint Selection -- An Autonomous Robotic System for Virtual Environment Creation}, author={Bourque, Eric and Dudek, Gregory}, booktitle={Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)}, pages={526--531}, year={1998}, address={Victoria, BC}, month={October} }

A mobile robot that learns its place

Oore; S.; Hinton; G. E.; Gregory Dudek

1997Neural Computation

Abstract

We show how a neural network can be used to allow a mobile robot to derive an accurate estimate of its location from noisy sonar sensors and noisy motion information. The robot's model of its location is in the form of a probability distribution across a grid of possible locations. This distribution is updated using both the motion information and the predictions of a neural network that maps locations into likelihood distributions across possible sonar readings. By predicting sonar readings from locations, rather than vice versa, the robot can

Topics

deep learninglocalizationslamsonar and acoustics

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@article{oore1997mobile,
 abstract = {We show how a neural network can be used to allow a mobile robot to derive an accurate estimate of its location from noisy sonar sensors and noisy motion information. The robot's model of its location is in the form of a probability distribution across a grid of possible locations. This distribution is updated using both the motion information and the predictions of a neural network that maps locations into likelihood distributions across possible sonar readings. By predicting sonar readings from locations, rather than vice versa, the robot can},
 author = {Oore, Sageev and Hinton, Geoffrey E and Dudek, Gregory},
 journal = {Neural Computation},
 number = {3},
 pages = {683--699},
 pub_year = {1997},
 publisher = {MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info~…},
 title = {A mobile robot that learns its place},
 venue = {Neural Computation},
 volume = {9}
}

Automated Creation of Image-Based Virtual Reality
Bourque; Eric; Gregory Dudek

1997Proc. SPIE Proceedings on Intelligent Systems and Manufacturing
Abstract
Abstract
Furthermore, selecting suitable vantage points to produce an evocative and complete VR model is in itself an important issue. This paper deals with the automated acquisition and construction of image-based VR models by having a robotic system select and acquire images from different vantage points. The objective is to provide a fully or partially automatic SE Chen, “QuickTime VR – An image based approach to virtual environment navigation,” in Proceedings of the ACM SIGGRAPH, pp. 29–38, ACM, (New York), 1995. 16.
Topics
complexity boundscomputer graphicsenvironment mappinggraph theoryimage matchinglocalizationplace recognitionslam
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@inproceedings{bourque1997automated, title={Automated Creation of Image-Based Virtual Reality}, author={Bourque, Eric and Dudek, Gregory}, booktitle={Proc. SPIE Proceedings on Intelligent Systems and Manufacturing}, pages={292--303}, year={1997}, address={Pittsburgh, PA}, month={Oct} }

Learning to Rendezvous during Multi-agent Exploration or What to do When You're Lost at the Zoo

Roy, Nicholas; Dudek, Gregory

1997Proc. of the Sixth European Workshop on Learning Robots (EWLR-6)

Abstract

Learning to Rendezvous during Multi-agent Exploration or What to do When You're Lost at the Zoo

Topics

complexity boundsgraph theorylocalizationrendezvousslam

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@inproceedings{roy1997learning,
  title={Learning to Rendezvous during Multi-agent Exploration or What to do When You're Lost at the Zoo},
  author={Roy, Nicholas and Dudek, Gregory},
  booktitle={Proc. of the Sixth European Workshop on Learning Robots (EWLR-6)},
  pages={30--45},
  year={1997},
  organization={AAAI},
  address={Brighton, UK},
  note={Also appears as the AAAI Workshop AAAI Technical Report WS-97-10},
  url={https://cdn.aaai.org/Workshops/1997/WS-97-10/WS97-10-004.pdf}
}

Learning to Rendezvous during Multi-agent Exploration or What to do When Youre Lost at the Zoo
Roy, Nicholas; Dudek, Gregory

1997Proc. of the Sixth European Workshop on Learning Robots (EWLR-6)
Abstract
Abstract
We consider the problem of rendezvous between two robots collaborating in learning the layout of an unknown environment. That is, how can two autonomous exploring agents that cannot communicate with one another over long distances meet if they start exploring at different locations in an unknown environment. The intended application is collaborative map exploration. Ours is the first work to formalize the characteristics of the rendezvous problem, and we approach it by proposing several alternative algorithms that the robots
Topics
complexity boundsexploration strategiesgraph theorylandmark-based methodslocalizationrendezvousslam
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BibTeX
@inproceedings{roy1997learning, title={Learning to Rendezvous during Multi-agent Exploration or What to do When Youre Lost at the Zoo}, author={Roy, Nicholas and Dudek, Gregory}, booktitle={Proc. of the Sixth European Workshop on Learning Robots (EWLR-6)}, pages={30--45}, year={1997}, month={Aug}, address={Brighton, UK} }

Map validation and robot self-location in a graph-like world

Jenkin; M.; Milios; E.; Wilkes; D.; Gregory Dudek

1997Robotics and autonomous systems

Abstract

This paper deals with the validation of topological maps of an environment by an active agent (such as a mobile robot), and the localization of an agent in a given map. The agent is assumed to have neither compass nor other instruments for measuring orientation or distance, and, therefore, no associated metrics. The topological maps considered are similar to conventional graphs. The robot is assumed to have enough sensory capability to traverse graph edges autonomously, recognize when it has reached a vertex, and enumerate edges

Topics

complexity boundsgraph theorylocalizationslamunderwater robotics

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@article{dudek1997map,
 abstract = {This paper deals with the validation of topological maps of an environment by an active agent (such as a mobile robot), and the localization of an agent in a given map. The agent is assumed to have neither compass nor other instruments for measuring orientation or distance, and, therefore, no associated metrics. The topological maps considered are similar to conventional graphs. The robot is assumed to have enough sensory capability to traverse graph edges autonomously, recognize when it has reached a vertex, and enumerate edges},
 author = {Dudek, Gregory and Jenkin, Michael and Milios, Evangelos and Wilkes, David},
 journal = {Robotics and autonomous systems},
 number = {2},
 pages = {159--178},
 pub_year = {1997},
 publisher = {Elsevier},
 title = {Map validation and robot self-location in a graph-like world},
 venue = {Robotics and autonomous systems},
 volume = {22}
}

Multi-Robot Exploration of an Unknown Environment: Efficiently Reducing the Odometry Error
Ioannis Rekleitis; Evangelos Milios; Gregory Dudek

1997Proc. International Joint Conference on Artificial Intelligence (IJCAI)
Abstract
Abstract
This paper deals with the intelligent exploration of an unknown environment by autonomous robots. In particular, we present an algorithm and associated analysis for collaborative exploration using two mobile robots. Our approach is based on robots with range sensors limited by distance. By appropriate behavioural strategies, we show that odometry (motion) errors that would normally present problems for mapping can be severely reduced. Our analysis includes polynomial complexity bounds and a discussion of possible heuristics. 1
Topics
complexity boundslocalizationslam
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@inproceedings{Rekleitis1997, author = {Ioannis Rekleitis and Evangelos Milios and Gregory Dudek}, title = {Multi-Robot Exploration of an Unknown Environment: Efficiently Reducing the Odometry Error}, booktitle = {Proc. International Joint Conference on Artificial Intelligence (IJCAI)}, year = {1997}, pages = {1340--1345}, address = {Nagoya, Japan}, month = sep }

On building and navigating with a globally topological but locally metric map

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1997Proc. 3rd ECPD Int. Conf. on Advanced Robotics, Intelligent Automation and Active Systems

Abstract

On building and navigating with a globally topological but locally metric map

Topics

complexity boundsgraph theorylocalizationslam

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BibTeX

@inproceedings{jenkin1997building,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {On building and navigating with a globally topological but locally metric map},
  booktitle = {Proc. 3rd ECPD Int. Conf. on Advanced Robotics, Intelligent Automation and Active Systems},
  year      = {1997},
  pages     = {132--144},
  address   = {Bremen, Germany}
}

On the Identification of Sonar Features
Lacroix; Simon; Gregory Dudek

1997Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
Abstract
Abstract
We are interested in inferring the sources of various types of sonar features typically observed by a mobile robot. After a brief discussion of terrestrial sonar sensing, we develop a set of operators that associates arc-shaped features extracted from sonar scans with real world primitives. Our classification scheme is probabilistic and is based on empirical data: the confidence of the association hypotheses produced by the operators is evaluated statistically. Some of our experimental results suggest that methods based on models of
Topics
localizationslamsonar and acoustics
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@inproceedings{lacroix1997identification, author = {Simon Lacroix and Gregory Dudek}, title = {On the Identification of Sonar Features}, booktitle = {Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)}, year = {1997}, pages = {586--592}, address = {Grenoble, France} }

On-line rendezvous selection for robot exploration

Roy; Nicholas; Gregory Dudek

1997Proc. American Association for Artificial Intelligence (AAAI) Workshop on On-Line Search

Abstract

On-line rendezvous selection for robot exploration

Topics

complexity boundslocalizationslam

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@inproceedings{roy1997online,
  title={On-line rendezvous selection for robot exploration},
  author={Roy, Nicholas and Dudek, Gregory},
  booktitle={Proc. American Association for Artificial Intelligence (AAAI) Workshop on On-Line Search},
  pages={22--29},
  year={1997},
  address={Providence, RI},
  note={Also available as AAAI Report WS-97-10}
}

On-line rendezvous selection for robot exploration or What to do When You're Lost at the Zoo

Roy, Nicholas; Dudek, Gregory

1997Proc. American Association for Artificial Intelligence (AAAI) Workshop on On-Line Search

Abstract

On-line rendezvous selection for robot exploration or What to do When YouÕre Lost at the Zoo

Topics

rendezvous

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@inproceedings{roy1997online,
  title={On-line rendezvous selection for robot exploration or What to do When You're Lost at the Zoo},
  author={Roy, Nicholas and Dudek, Gregory},
  booktitle={Proc. American Association for Artificial Intelligence (AAAI) Workshop on On-Line Search},
  pages={22--29},
  year={1997},
  address={Providence, RI},
  note={Also available as AAAI Report WS-97-10},
  url={https://cdn.aaai.org/Workshops/1997/WS-97-10/WS97-10-004.pdf}
}

On-line rendezvous selection for robot exploration or What to do When You're Lost at the Zoo

Roy, Nicholas; Dudek, Gregory

1997Proc. American Association for Artificial Intelligence (AAAI) Workshop on On-Line Search

Abstract

On-line rendezvous selection for robot exploration or What to do When YouÕre Lost at the Zoo

Topics

rendezvous

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BibTeX

@inproceedings{roy1997online,
  title={On-line rendezvous selection for robot exploration or What to do When You're Lost at the Zoo},
  author={Roy, Nicholas and Dudek, Gregory},
  booktitle={Proc. American Association for Artificial Intelligence (AAAI) Workshop on On-Line Search},
  pages={22--29},
  year={1997},
  address={Providence, RI},
  note={Also available as AAAI Report WS-97-10},
  url={https://cdn.aaai.org/Workshops/1997/WS-97-10/WS97-10-004.pdf}
}

Reducing odometry error through cooperating robots during the exploration of an unknown world
Ioannis Rekleitis; Evangelos Milios; Gregory Dudek

1997Proc. Fifth IASTED International Conference ROBOTICS AND MANUFACTURING
Abstract
Abstract
We consider how to cover and map an initially unknown environment using two (or more) mobile robots. Most mobile robot systems accrue odometry error while moving, and hence need to use external sensors to recalibrate their position on an ongoing basis. Unfortunately, most sensing systems are constrained with respect to the types of environment in which they are suitable. We deal with position calibration and odometry error by using multiple robots for exploration. This allows them to use one another as landmarks. We consider how
Topics
complexity boundscooperative localizationexploration strategiesgraph theorylandmark-based methodslocalizationrobotic collectivesslam
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@inproceedings{Rekleitis1997, author = {Ioannis Rekleitis and Evangelos Milios and Gregory Dudek}, title = {Reducing odometry error through cooperating robots during the exploration of an unknown world}, booktitle = {Proc. Fifth IASTED International Conference ROBOTICS AND MANUFACTURING}, year = {1997}, month = {June}, pages = {200--208} }

Shape representation and recognition from multiscale curvature

Tsotsos; John K.; Gregory Dudek

1997Computer Vision, Graphics and Image Processing: Image Understanding

Abstract

Shape Representation and Recognition from Curvature

Topics

curvatureshape

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@article{Tsotsos1997,
  title={Shape representation and recognition from multiscale curvature},
  author={Tsotsos, John K. and Dudek, Gregory},
  journal={Computer Vision, Graphics and Image Processing: Image Understanding},
  volume={68},
  number={2},
  year={1997},
  pages={170--189}
}

Shape representation and recognition from multiscale curvature

Tsotsos; John K.; Gregory Dudek

1997Computer Vision, Graphics and Image Processing: Image Understanding

Abstract

Shape Representation and Recognition from Curvature

Topics

curvatureshape

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BibTeX

@article{Tsotsos1997,
  title={Shape representation and recognition from multiscale curvature},
  author={Tsotsos, John K. and Dudek, Gregory},
  journal={Computer Vision, Graphics and Image Processing: Image Understanding},
  volume={68},
  number={2},
  year={1997},
  pages={170--189}
}

A Hybrid Approach to 3D Representation
Ayoung-Chee; Nigel; Ferrie; Frank; Gregory Dudek

1996Proceedings of the IEEE International Workshop on Object Representation
Abstract
Abstract
This paper deals with generic 3D shape modelling for the purposes of object recognition. Common problems with many existing methods are that they either capture insufficient detailed structure or fail to provide sufficiently abstract descriptions (global vs. local representation). As a result, they tend have a limited field of application. The approach presented here attempts to address this problem by building a composite representation of the data in terms of a superquadric augmented with multi-scale surface models. This is
Topics
object recognition
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@inproceedings{ayoung1996hybrid, title={A Hybrid Approach to 3D Representation}, author={Ayoung-Chee, Nigel and Ferrie, Frank and Dudek, Gregory}, booktitle={Proceedings of the IEEE International Workshop on Object Representation}, pages={202--209}, year={1996}, address={Cambridge, England} }

A taxonomy for multi-agent robotics

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1996Autonomous Robots

Abstract

A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multi-agent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent

Topics

cooperative localizationlocalizationrobotic collectivesslam

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@article{dudek1996taxonomy,
 abstract = {A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multi-agent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent},
 author = {Dudek, Gregory and Jenkin, Michael RM and Milios, Evangelos and Wilkes, David},
 journal = {Autonomous Robots},
 pages = {375--397},
 pub_year = {1996},
 publisher = {Springer},
 title = {A taxonomy for multi-agent robotics},
 venue = {Autonomous Robots},
 volume = {3}
}

Enhanced 3D Representation Using a Hybrid Model
Ayoung-Chee; Nigel; Ferrie; Frank; Gregory Dudek

1996Proc. International Conf. on Pattern Recognition
Abstract
Abstract
This paper deals with generic 3D shape modelling for the purposes of object recognition. Difficulties with many existing methods are that they either capture insufficient detailed structure or fail to provide sufficiently abstract descriptions. The approach presented here attempts to address this problem by building a composite representation of the data in terms of a superquadric augmented with multi-scale surface models. This is illustrated experimentally using laser range data. The superquadric that results in the best possible fit
Topics
3d reconstructioncurvatureobject recognitionshapevariational methods
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BibTeX
@inproceedings{Ayoung-Chee1996, author = {Nigel Ayoung-Chee and Frank Ferrie and Gregory Dudek}, title = {Enhanced 3D Representation Using a Hybrid Model}, booktitle = {Proc. International Conf. on Pattern Recognition}, year = {1996}, address = {Vienna, Austria}, month = {August}, pages = {575--579} }
Enhanced 3D Representation Using a Hybrid Model
Nigel Ayoung-Chee; Frank Ferrie; Gregory Dudek

1996Proc. International Conf. on Pattern Recognition
Abstract
Abstract
This paper deals with generic 3D shape modelling for the purposes of object recognition. Difficulties with many existing methods are that they either capture insufficient detailed structure or fail to provide sufficiently abstract descriptions. The approach presented here attempts to address this problem by building a composite representation of the data in terms of a superquadric augmented with multi-scale surface models. This is illustrated experimentally using laser range data. The superquadric that results in the best possible fit
Topics
3d reconstructioncurvatureobject recognitionshapevariational methods
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BibTeX
@inproceedings{Ayoung-Chee1996, author = {Nigel Ayoung-Chee and Frank Ferrie and Gregory Dudek}, title = {Enhanced 3D Representation Using a Hybrid Model}, booktitle = {Proc. International Conf. on Pattern Recognition}, year = {1996}, address = {Vienna, Austria}, month = {August}, pages = {575--579} }
Environment Mapping Using ``Just-In-Time'' Sensor Fusion
Freedman; Paul; Rekleitis; Ioannis; Gregory Dudek;

1996Proceedings of Vision Interface
Abstract
Abstract
Environment Mapping Using ``Just-In-Time
Topics
complexity boundsenvironment mappinglocalizationslamunderwater robotics
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@inproceedings{freedman1996environment, title={Environment Mapping Using ``Just-In-Time'' Sensor Fusion}, author={Freedman, Paul and Rekleitis, Ioannis and Dudek, Gregory}, booktitle={Proceedings of Vision Interface}, pages={96--103}, year={1996}, address={Toronto, ON}, month={April} }

Environment mapping using multiple abstraction levels

Dudek; Gregory

1996Proceedings of the IEEE

Abstract

Environment mapping using multiple abstraction levels

Topics

environment mapping

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@article{dudek1996environment,
  title={Environment mapping using multiple abstraction levels},
  author={Dudek, Gregory},
  journal={Proceedings of the IEEE},
  volume={84},
  number={11},
  pages={1684--1704},
  year={1996},
  month={Nov},
  note={Special issue on ``Signals and Symbols''}
}

Just-in-Time Sensing: Efficiently Combining Sonar and Laser Range Data for Exploring Unknown Worlds
Gregory Dudek; Paul Freedman; Yiannis Rekleitis

1996Proceedings IEEE International Conference on Robotics and Automation
Abstract
Abstract
This paper describes an approach to combining range data from both a set of sonar sensors as well as from a directional laser range finder to efficiently take advantage of the characteristics of both types of devices when exploring and mapping unknown worlds. The authors call their approach" just in time sensing" because it uses the more accurate but constrained laser range sensor only as needed, based upon a preliminary interpretation of sonar data. In this respect, it resembles" just in time" inventory control which attempts to
Topics
environment mappingexploration strategieslocalizationslamunderwater robotics
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@inproceedings{dudek1996just, author = {Gregory Dudek and Paul Freedman and Yiannis Rekleitis}, title = {Just-in-Time Sensing: Efficiently Combining Sonar and Laser Range Data for Exploring Unknown Worlds}, booktitle = {Proceedings IEEE International Conference on Robotics and Automation}, year = {1996}, volume = {1}, pages = {667--672}, address = {Minneapolis, MN}, month = apr }
Mobile Robot Navigation: A Case Study
Roy; Nicholas; Daum; Michael; Gregory Dudek

1996Proc. American Assoc. for Artificial Intelligence National Conf. on Artificial Intelligence (AAAI)
Abstract
Abstract
Mobile Robot Navigation: A Case Study
Topics
complexity boundslocalizationslam
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BibTeX
@inproceedings{roy1996mobile, title={Mobile Robot Navigation: A Case Study}, author={Roy, Nicholas and Daum, Michael and Dudek, Gregory}, booktitle={Proc. American Assoc. for Artificial Intelligence National Conf. on Artificial Intelligence (AAAI)}, year={1996} }
Shape from Darkness in Three Dimensions Using Information from Solar Trajectories
Michael Daum; Gregory Dudek

1996Proc. US/Japan Student Forum (in affiliation with RSJ/IEEE IROS conference)
Abstract
Abstract
Shape from Darkness in Three Dimensions Using Information from Solar Trajectories
Topics
3d reconstructioncomplexity boundsgraph theorylocalizationslam
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BibTeX
@inproceedings{daum1996shape, author = {Michael Daum and Gregory Dudek}, title = {Shape from Darkness in Three Dimensions Using Information from Solar Trajectories}, booktitle = {Proc. US/Japan Student Forum (in affiliation with RSJ/IEEE IROS conference)}, year = {1996}, address = {Nagoya, Japan}, pages = {20} }

Shape integration for visual object recognition and its implication in category-specific visual agnosia

Arguin, Martin

1996Visual cognition

Abstract

A series of experiments was conducted on a patient (ELM) with bilateral inferior temporal lobe damage and category-specific visual agnosia in order to specify the nature of his functional impairment. In Experiment 1, ELM performed a task of picture/word matching that used line drawings of fruits and vegetables as stimuli. The pattern of confusions exhibited by the patient suggested a failure in processing the full range of shape features necessary for the unique specification of the target relative to other structurally related items. This

Topics

object recognitionshapevisual agnosia

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@article{arguin1996shape,
 abstract = {A series of experiments was conducted on a patient (ELM) with bilateral inferior temporal lobe damage and category-specific visual agnosia in order to specify the nature of his functional impairment. In Experiment 1, ELM performed a task of picture/word matching that used line drawings of fruits and vegetables as stimuli. The pattern of confusions exhibited by the patient suggested a failure in processing the full range of shape features necessary for the unique specification of the target relative to other structurally related items. This},
 author = {Arguin, Martin},
 journal = {Visual cognition},
 number = {3},
 pages = {221--276},
 pub_year = {1996},
 publisher = {Taylor \& Francis},
 title = {Shape integration for visual object recognition and its implication in category-specific visual agnosia},
 venue = {Visual cognition},
 volume = {3}
}

Surface Sensing and Classification for Efficient Mobile Robot Navigation
Roy, Nicholas; Freedman, Paul; Dudek, Gregory

1996Proceedings IEEE International Conference on Robotics and Automation
Abstract
Abstract
Mobile robot navigation and localization is frequently aided by, or even dependent upon, a good estimate of the rate of dead-reckoning error accumulation. Sensor data can be used for position estimation, but this often involves overheads in acquiring and processing the data. By sensing and then classifying the surface type, an estimate of the rate of error accumulation for dead-reckoning allows one to estimate accurately how often localization, including sensor data acquisition, must be performed. The authors describe experiments in
Topics
localizationslamsonar and acoustics
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BibTeX
@inproceedings{roy1996surface, title={Surface Sensing and Classification for Efficient Mobile Robot Navigation}, author={Roy, Nicholas and Freedman, Paul and Dudek, Gregory}, booktitle={Proceedings IEEE International Conference on Robotics and Automation}, volume={2}, pages={1224--1228}, year={1996}, address={Minneapolis, MN}, month={April} }

Using multiple models for environmental mapping

Hadjres; Souad; Freedman; Paul; Gregory Dudek

1996Journal of Robotic Systems

Abstract

Topics

complexity boundsgraph theorylocalizationslamunderwater robotics

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@article{dudek1996using,
 abstract = {},
 author = {Dudek, Gregory and Freedman, Paul and Hadjres, Souad},
 journal = {Journal of Robotic Systems},
 number = {8},
 pages = {539--559},
 pub_year = {1996},
 title = {Using multiple models for environmental mapping},
 venue = {NA},
 volume = {13}
}

Vision-based Robot Localization Without Explicit Object Models
Zhang; Chi; Gregory Dudek

1996Proceedings IEEE International Conference on Robotics and Automation
Abstract
Abstract
We consider the problem of locating a robot in an initially-unfamiliar environment from visual input. The robot is not given a map of the environment, but it does have access to a collection of training examples, each of which specifies the video image observed when the robot is at a particular location and orientation. We address two variants of this problem: how to estimate translation of a moving robot assuming the orientation is known, and how to estimate translation and orientation for a mobile robot. Performing scene reconstruction to
Topics
landmark-based methodslocalizationslam
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@inproceedings{zhang1996vision, title={Vision-based Robot Localization Without Explicit Object Models}, author={Zhang, Chi and Dudek, Gregory}, booktitle={Proceedings IEEE International Conference on Robotics and Automation}, volume={1}, pages={76--82}, year={1996}, organization={IEEE}, address={Minneapolis, MN}, month={April} }
Experiments in sensing and communication for robot convoy navigation
Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1995Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
Abstract
Abstract
This paper deals with coordinating behaviour in a multi-autonomous robot system. When two or more autonomous robots must interact in order to accomplish some common goal, communication between the robots is essential. Different inter-robot communications strategies give rise to different overall system performance and reliability. After a brief consideration of some theoretical approaches to multiple robot collections, we present concrete implementations of different strategies for convoy-like behaviour. The convoy
Topics
cooperative localizationlocalizationrobotic collectives
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@inproceedings{jenkin1995experiments, author = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek}, title = {Experiments in sensing and communication for robot convoy navigation}, booktitle = {Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)}, year = {1995}, volume = {2}, pages = {268--273}, address = {Pittsburgh, PA}, month = {August} }

Exploring Graph-Like World Embedded in a Metric Map

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1995Proc. Vision Interface

Abstract

Exploring Graph-Like World Embedded in a Metric Map

Topics

complexity boundsgraph theorylocalizationslam

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@inproceedings{jenkin1995exploring,
  title={Exploring Graph-Like World Embedded in a Metric Map},
  author={Jenkin, Michael and Milios, Evangelos and Wilkes, David and Dudek, Gregory},
  booktitle={Proc. Vision Interface},
  pages={195--202},
  year={1995},
  address={Quebec City, Que.},
  month={July}
}

Localizing a Robot with Minimum Travel
Romanik; Kathleen; Whitesides; Sue; Gregory Dudek

1995SIAM Symposium on Discrete Algorithms (SODA)
Abstract
Abstract
We consider the problem of localizing a robot in a known environment modeled by a simple polygon P. We assume that the robot has a map of P but is placed at an unknown location inside P. From its initial location, the robot sees a set of points called the visibility polygon V of its location. In general, sensing at a single point will not suffice to uniquely localize the robot, since the set H of points in P with visibility polygon V may have more than one element. Hence, the robot must move around and use range sensing and a compass to
Topics
complexity boundslocalizationpath planningslam
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@inproceedings{romanik1995localizing, title={Localizing a Robot with Minimum Travel}, author={Romanik, Kathleen and Whitesides, Sue and Dudek, Gregory}, booktitle={SIAM Symposium on Discrete Algorithms (SODA)}, pages={437--446}, year={1995}, month={Jan} }

Multi-robot landmark-based self-location and exploration

Michael Jenkin; Evangelos Milios; David Wilkes; Gregory Dudek

1995Proc. Third Int. Symposium on Intelligent Robotic Systems (SIRS)

Abstract

Multi-robot landmark-based self-location and exploration

Topics

complexity boundsexploration strategieslandmark-based methodslocalizationslam

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@inproceedings{jenkin1995multi,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {Multi-robot landmark-based self-location and exploration},
  booktitle = {Proc. Third Int. Symposium on Intelligent Robotic Systems (SIRS)},
  year      = {1995},
  pages     = {49--56},
  address   = {Pisa, Italy},
  month     = {July}
}

Space occupancy using multiple shadowimages
Langer; Michael; Zucker; Steven W.; Gregory Dudek

1995Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
Abstract
Abstract
Addresses the problem of estimating 3D space occupancy using video imagery in the context of mobile robotics. A stationary robot observes a cluttered scene from a single viewpoint, and a second robot illuminates the scene from a sequence of directions thus producing a sequence of grey-level images. Differences of successive images are used to compute a sequence of shadowimages. The problem is to compute free space and occupied space from these shadowimages. Solutions to this problem are known for the special case of
Topics
3d reconstruction
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@inproceedings{langer1995space, title={Space occupancy using multiple shadowimages}, author={Langer, Michael and Zucker, Steven W. and Dudek, Gregory}, booktitle={Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)}, volume={1}, pages={285--290}, year={1995}, address={Pittsburgh, PA}, month={August} }
Understanding Referring Expressions in a Person-Machine Spoken Dialogue
Pateras; Claudia; DeMori; Renato; Gregory Dudek

1995Proc. of the IEEE Conference of Acoustics, Speech and Signal Processing
Abstract
Abstract
In the domain of mobile robotic task execution under dialogue control, a primary goal is to identify the task target which is specified by a natural language description. A number of concepts are expressed in the user spoken language by vague terms like" the big box" and" very close to the door". We use fuzzy logic to map these vague terms onto the quantitative data collected by system sensors. Fuzziness may cause uncertainty in interpretation and, in particular, in understanding references. This uncertainty is abated by collecting additional
Topics
generative aihuman-robot interactionlocalizationreinforcement learningslam
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@inproceedings{pateras1995understanding, title={Understanding Referring Expressions in a Person-Machine Spoken Dialogue}, author={Pateras, Claudia and DeMori, Renato and Dudek, Gregory}, booktitle={Proc. of the IEEE Conference of Acoustics, Speech and Signal Processing}, pages={197--200}, year={1995}, address={Detroit, MI}, month={April} }

Dimensional Decomposition of Human Shape Recognition

Arguin; Martin; Bub; Daniel; Gregory Dudek

1994Investigative Ophthalmology and Visual Science (Suppl)

Abstract

Dimensional Decomposition of Human Shape Recognition

Topics

curvaturegenerative aigesture-based interactionobject recognitionshapevariational methods

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BibTeX

@article{Arguin1994,
  author    = {Martin Arguin and Daniel Bub and Gregory Dudek},
  title     = {Dimensional Decomposition of Human Shape Recognition},
  journal   = {Investigative Ophthalmology and Visual Science (Suppl)},
  year      = {1994},
  publisher = {The Association for Research in Vision and Opthalmology},
  address   = {Sarasota, FL},
  month     = {May}
}

Horoptor and active cyclotorsion
Jenkin; Michael; Tsotsos; J. K.; Gregory Dudek

1994Proceedings of the International Conference on Pattern Recognition
Abstract
Abstract
When a particular 3D point is fixated by a robotic stereo system different portions of the world are brought into interocular alignment. This region is known as the horoptor. Purposeful modifications to the binocular geometry can be used to bring different regions of three-space closer to the horoptor: camera pan and tilt define the rough structure of the horoptor, while camera torsion can be used to change its local shape. Theoretical and empirical results suggest that for binocular vision tasks: 1) it is important to understand the region of three
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@inproceedings{jenkin1994horoptor, author = {Michael Jenkin and J. K. Tsotsos and Gregory Dudek}, title = {Horoptor and active cyclotorsion}, booktitle = {Proceedings of the International Conference on Pattern Recognition}, year = {1994}, volume = {1}, pages = {707--710} }
Human Integration of Shape Primitives
Arguin; Martin; Bub; Daniel; Gregory Dudek

1994Proceedings of the International Workshop on Visual Form
Abstract
Abstract
This paper deals with human shape recognition. In particular, we present results relating the role of human inferior temporal cortex to the description and recognition of shapes using a parametric three-dimensional shape space. In experiments with a patient with damaged IT cortex, we show that his inability to recognize or distinguish between members of a large family of simple shapes can be traced to an inability to simultaneously combine information related to multiple global shape dimensions. We have discovered that the relevant
Topics
object recognition
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@inproceedings{Arguin1994, author = {Martin Arguin and Daniel Bub and Gregory Dudek}, title = {Human Integration of Shape Primitives}, booktitle = {Proceedings of the International Workshop on Visual Form}, year = {1994}, pages = {130--138}, address = {Capri, Italy}, month = {May} }
Mapping Unknown Graph-Like Worlds
Freedman; Paul; Gregory Dudek

1994Proceedings of the International Advanced Robotics Programme Workshop on Robotics in Space
Abstract
Abstract
We consider the problem of constructing a map of an unknown environment by an autonomous agent such as a mobile robot. Because accurate positional information is often difficult to ensure, we consider the problem of exploration in the absence of metric (positional) information. Worlds are represented by graphs (not necessarily planar) consisting of a fixed number of discrete places linked by bidirectional paths. We assume the robot can consistently enumerate the edges leaving a vertex (that is, it can assign a cyclic
Topics
complexity boundsgraph theorylocalizationslam
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@inproceedings{freedman1994mapping, title={Mapping Unknown Graph-Like Worlds}, author={Freedman, Paul and Dudek, Gregory}, booktitle={Proceedings of the International Advanced Robotics Programme Workshop on Robotics in Space}, pages={1--20}, year={1994}, address={Montreal, Canada}, month={July} }
Multi-scale object representation using surface patches
Alami; Wassim; Gregory Dudek

1994Proceedings of the International Society for Optical Engineering
Abstract
Abstract
We introduce an approach to the representation of curved or polyhedral 3-D objects and apply this representation to pose estimation. The representation is based on surface patches with uniform curvature properties extracted at multiple scales. These patches are computed using multiple alternative decompositions of the surface based on the signs of the mean and Gaussian curvatures. Initial coarse decompositions are subsequently refined using a curvature compatibility scheme to rectify the effect of noise and quantization errors. The
Topics
3d reconstructioncurvatureobject recognitionshapevariational methods
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@inproceedings{alami1994multi, title={Multi-scale object representation using surface patches}, author={Alami, Wassim and Dudek, Gregory}, booktitle={Proceedings of the International Society for Optical Engineering}, volume={2353}, pages={108--119}, year={1994} }
Pose Estimation From Image Data Without Explicit Object Models
Zhang, Chi; Dudek, Gregory

1994Proceedings of Vision Interface
Abstract
Abstract
We consider the problem of locating a robot in an initially-unfamiliar environment from visual input. The robot is not given a map of the environment, but it does have access to a limited set of training examples each of which specifies the video image observed when the robot is at a particular location and orientation. Such data might be acquired using dead reckoning the first time the robot entered an unfamiliar region (using some simple mechanism such as sonar to avoid collisions). In this paper, we address a specific variant of this problem for
Topics
localization
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@inproceedings{zhang1994pose, title={Pose Estimation From Image Data Without Explicit Object Models}, author={Zhang, Chi and Dudek, Gregory}, booktitle={Proceedings of Vision Interface}, year={1994}, month={May}, address={Banff, Alta.} }
Precise Positioning Using Model-Based Maps
MacKenzie; Paul; Gregory Dudek

1994Proceedings of the 1994 IEEE International Conference on Robotics and Automation
Abstract
Abstract
This paper addresses the coupled tasks of constructing a spatial representation of the environment with a mobile robot using noisy sensors (sonar) and using such a map to determine the robot's position. The map is not meant to represent the actual spatial structure of the environment so much as it is meant to represent the major structural components of what the robot" sees". This can, in turn, be used to construct a model of the physical objects in the environment. One problem with such an approach is that maintaining an absolute
Topics
localizationslamsonar and acoustics
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@inproceedings{MacKenzie1994, author = {Paul MacKenzie and Gregory Dudek}, title = {Precise Positioning Using Model-Based Maps}, booktitle = {Proceedings of the 1994 IEEE International Conference on Robotics and Automation}, year = {1994}, pages = {1615--1621}, address = {San Diego, CA}, month = {May} }

A Multi-Layer Distributed Environment for Mobile Robots

Jenkin; Michael; Gregory Dudek

1993Proceedings of the International Conference on Intelligent Autonomous Systems: IAS-3

Abstract

A Multi-Layer Distributed Environment for Mobile Robots

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@inproceedings{jenkin1993multi,
  author    = {Michael Jenkin and Gregory Dudek},
  title     = {A Multi-Layer Distributed Environment for Mobile Robots},
  booktitle = {Proceedings of the International Conference on Intelligent Autonomous Systems: IAS-3},
  year      = {1993},
  address   = {Pittsburgh, PA},
  month     = feb,
  pages     = {542--550}
}

A Taxonomy for swarm robotics

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1993Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)

Abstract

A Taxonomy for swarm robotics

Topics

complexity bounds

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@inproceedings{jenkin1993taxonomy,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {A Taxonomy for swarm robotics},
  booktitle = {Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)},
  year      = {1993},
  pages     = {441--447},
  address   = {Yokohama, Japan},
  month     = {July}
}

Map validation and self-location in a graph-like world
Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1993Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93)
Abstract
Abstract
We present algorithms for the discovery and use of topological maps of an environment by an active agent (such as a person or a mobile robot). We discuss several issues dealing with the use of pre-existing topological maps of graph-like worlds by an autonomous robot and present algorithms, worst cases complexity, and experimental results (for representative real-world examples) for two key problems. The first of these problems is to verify that a given input map is a correct description of the world (the validation problem). The second is to
Topics
complexity boundsgraph theorylocalization
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@inproceedings{jenkin1993map, title={Map validation and self-location in a graph-like world}, author={Jenkin, Michael and Milios, Evangelos and Wilkes, David and Dudek, Gregory}, booktitle={Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93)}, pages={1648--1653}, year={1993}, address={Chambery, France}, month={August} }

Model Based Map Construction for Mobile Robot Localization

MacKenzie; Paul; Gregory Dudek

1993Proceedings of Vision Interface '93

Abstract

Model Based Map Construction for Mobile Robot Localization

Topics

complexity boundslocalizationslam

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@inproceedings{MacKenzie1993,
  author    = {Paul MacKenzie and Gregory Dudek},
  title     = {Model Based Map Construction for Mobile Robot Localization},
  booktitle = {Proceedings of Vision Interface '93},
  year      = {1993},
  address   = {Toronto, Ontario},
  month     = {July},
  pages     = {97--102}
}

Multi-Transducer Sonar Interpretation
Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1993Proceedings of the 1993 IEEE International Conference on Robotics and Automation
Abstract
Abstract
In response to difficulties with interpretation of data from narrow beam time-of-flight sonar for robotics, an algorithm for sonar interpretation that uses the entire return signals from several transducers with broad, overlapping fields of view is presented. The result is an algorithm that reconstructs the geometry in front of the robot with only a moderate amount of robot motion. Preliminary results with a three transducer system are shown. The results demonstrate an unusual ability to recover the presence of obstacles even when they are
Topics
bayesian inferencesonar and acousticsunderwater navigation
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@inproceedings{jenkin1993multi, author = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek}, title = {Multi-Transducer Sonar Interpretation}, booktitle = {Proceedings of the 1993 IEEE International Conference on Robotics and Automation}, year = {1993}, pages = {392--397}, address = {Atlanta, GA}, month = {May} }

On the Utility of Multi-Agent Autonomous Robot Systems

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1993Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93) Workshop on Dynamically Interacting Robots

Abstract

Topics

complexity boundscooperative localizationgraph theorylocalizationrendezvousrobotic collectivesslamtelecommunications

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@inproceedings{jenkin1993utility,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {On the Utility of Multi-Agent Autonomous Robot Systems},
  booktitle = {Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93) Workshop on Dynamically Interacting Robots},
  year      = {1993},
  address   = {Chambery, France},
  pages     = {101--108}
}

Organizational Characteristics for Multi-Agent Robotic Systems

Dudek; Gregory; Michael Jenkin; Evangelos Milios; David Wilkes

1993Proceedings of Vision Interface '93

Abstract

Topics

complexity boundsgenerative aigraph theorylocalizationslamtelecommunicationsunderwater robotics

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@inproceedings{dudek1993organizational,
  author    = {Gregory Dudek and Michael Jenkin and Evangelos Milios and David Wilkes},
  title     = {Organizational Characteristics for Multi-Agent Robotic Systems},
  booktitle = {Proceedings of Vision Interface '93},
  year      = {1993},
  address   = {Toronto, Ontario},
  month     = {July},
  pages     = {91--96}
}

Reflections on Sonar Range Sensing
Dudek; Gregory; Michael Jenkin; Evangelos Milios; David Wilkes

1993CIM
Abstract
Abstract
Reflections on Sonar Range Sensing
Topics
sonar and acousticsunderwater navigationunderwater robotics
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@techreport{Dudek1993, author = {Gregory Dudek and Michael Jenkin and Evangelos Milios and David Wilkes}, title = {Reflections on Sonar Range Sensing}, institution = {CIM}, number = {CIM-92-9}, year = {1993}, month = {December 21} }
Robust Positioning with a Multi-Agent Robotic System
Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1993Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93) Workshop on Dynamically Interacting Robots
Abstract
Abstract
A collection of interacting autonomous robots can de ne a local coordinate system with respect to one another without reference to environmental features. This simpli es tasks requiring robots to occupy or traverse a set of positions in the environment, such as mapping, conveyance and search. We argue for an approach to positioning in which sensing errors remain localized, and dead-reckoning plays no role. This involves a robot-based representation for the environment, in which metric information is used locally to
Topics
complexity boundscooperative localizationexploration strategiesgraph theorylocalizationrendezvousrobotic collectivesslamtelecommunications
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@inproceedings{jenkin1993robust, author = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek}, title = {Robust Positioning with a Multi-Agent Robotic System}, booktitle = {Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93) Workshop on Dynamically Interacting Robots}, year = {1993}, pages = {118--123}, address = {Chambery, France}, month = {August} }
Using local information in a non-local way for mapping graph-like worlds
Souad Hadjres; Paul Freedman; Gregory Dudek

1993Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93)
Abstract
Abstract
This paper describes a technique whereby an autonomous agent such as a mobile robot can explore an unknown environment and make a topological map of it. It is assumed that the environment can be represented as a graph, that is, as a xed set of discrete locations or regions with an ordered set of paths between them. In previous work, it has been shown that such worlds can be fully explored and described using a single movable marker even if there are no spatial metrics and almost no sensory ability on the part of the robot. Here we
Topics
complexity boundscooperative localizationgraph theorylocalizationrobotic collectivesslam
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@inproceedings{Hadjres1993, author = {Souad Hadjres and Paul Freedman and Gregory Dudek}, title = {Using local information in a non-local way for mapping graph-like worlds}, booktitle = {Proceedings of the International Joint Conference of Artificial Intelligence (IJCAI-93)}, year = {1993}, pages = {1639--1645}, address = {Chambery, France}, month = {August} }
Algorithms for Active Exploration of Unknown Environments: Using Uncertain Sensing Data to Create a Reliable Map
Souad Hadjres; Paul Freedman; Gregory Dudek

1992Proceedings of the International Society for Optical Engineering Symposium on Advances in Intelligent Robotics Systems: Conference on Mobile Robotics VII
Abstract
Abstract
Algorithms for Active Exploration of Unknown Environments: Using Uncertain Sensing Data to Create a Reliable Map
Topics
complexity boundsexploration strategiesgraph theorylocalizationslam
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@inproceedings{Hadjres1992, author = {Souad Hadjres and Paul Freedman and Gregory Dudek}, title = {Algorithms for Active Exploration of Unknown Environments: Using Uncertain Sensing Data to Create a Reliable Map}, booktitle = {Proceedings of the International Society for Optical Engineering Symposium on Advances in Intelligent Robotics Systems: Conference on Mobile Robotics VII}, address = {Boston, MA}, month = {November}, year = {1992} }

Modelling Sonar Range Sensors

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1992Advances in Machine Vision: Strategies and Applications

Abstract

Modelling Sonar Range Sensors

Topics

sonar and acousticsunderwater navigationunderwater robotics

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@incollection{jenkin1992modelling,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {Modelling Sonar Range Sensors},
  booktitle = {Advances in Machine Vision: Strategies and Applications},
  editor    = {C. Archibald and E. Petriu},
  publisher = {World Scientific Press},
  address   = {Singapore},
  year      = {1992},
  pages     = {361--370}
}

Robot Map-Making Using Weak Sensory Feedback
Dudek; Gregory

1992Proceedings of the Workshop on Sensor-Based Mobile Robotics
Abstract
Abstract
Robot Map-Making Using Weak Sensory Feedback
Topics
complexity boundsgraph theorylocalizationslam
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@inproceedings{dudek1992robot, author = {Gregory Dudek}, title = {Robot Map-Making Using Weak Sensory Feedback}, booktitle = {Proceedings of the Workshop on Sensor-Based Mobile Robotics}, address = {Nice, France}, month = {May}, year = {1992} }

Shape Classification and Scale-Space Texture

Dudek; Gregory

1992Investigative Ophthalmology and Visual Science (Suppl)

Abstract

Topics

bayesian inferencecomplexity boundsdeep learninggraph theorymarkov chain monte carlomarkov random fieldsobject recognitiontexturewavelet analysis

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@article{dudek1992shape,
  author = {Gregory Dudek},
  title = {Shape Classification and Scale-Space Texture},
  journal = {Investigative Ophthalmology and Visual Science (Suppl)},
  year = {1992},
  publisher = {The Association for Research in Vision and Ophthalmology},
  address = {Sarasota, FL},
  month = {May}
}

Shape Description and Classification using Scale-Space Measurement

Dudek; Gregory

1992Proceedings of the Workshop on Shape in Picture

Abstract

Shape Description and Classification using Scale-Space Measurement

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@inproceedings{dudek1992shape,
  author    = {Gregory Dudek},
  title     = {Shape Description and Classification using Scale-Space Measurement},
  booktitle = {Proceedings of the Workshop on Shape in Picture},
  year      = {1992},
  address   = {Driebergen, Holland},
  month     = {August},
  note      = {Revised manuscript to appear in the book Shape in Picture published by Springer Verlag}
}

Using Curvature Information in the Decomposition and Representation of Planar Curves
John K. Tsotsos; Gregory Dudek

1992Active Perception and Robot Vision
Abstract
Abstract
This paper describes a new symbolic representation for planar curves. This representation is based on a segmentation of the curve based on regions of uniform curvature. Rather than smooth noisy data before doing the decomposition, the technique defines a family of functions that extract the segments of the curve as part of the smoothing process. The representation decomposes the curve at multiple scales and the parts produced appear to correspond to a natural decomposition of the curve. It also allows for multiple descriptions of
Topics
curvatureshapevariational methods
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@incollection{tsotsos1992using, author = {John K. Tsotsos and Gregory Dudek}, title = {Using Curvature Information in the Decomposition and Representation of Planar Curves}, booktitle = {Active Perception and Robot Vision}, editor = {A. Sood and H. Wechsler}, publisher = {Springer-Verlag}, year = {1992}, pages = {527--536} }

Robustly recognizing curves using curvature-tuned smoothing

Tsotsos; John K.; Gregory Dudek

19911991 IEEE Conference on Computer Vision and Pattern Recognition

Abstract

Robustly recognizing curves using curvature-tuned smoothing

Topics

curvatureshape

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@inproceedings{tsotsos1991robustly,
  title={Robustly recognizing curves using curvature-tuned smoothing},
  author={Tsotsos, John K. and Dudek, Gregory},
  booktitle={1991 IEEE Conference on Computer Vision and Pattern Recognition},
  pages={35--41},
  year={1991},
  organization={IEEE},
  address={Maui, HI},
  month={July}
}

Shape Metrics From Curvature Scale-Space and Curvature-Tuned Smoothing
Dudek; Gregory

1991Proceedings of the Conference on Geometric Methods in Computer Vision
Abstract
Abstract
This research deals with the decomposition and description of curved objects. In ongoing work, a new part description for curves and surfaces using a set of curvature-based minimization operators has been developed. The decomposition operation simultaneously performs data interpolation, data smoothing, and segmentation. The unification of these three stages results in a smoothing operation that is tightly coupled with the primitives to be used in subsequent object description. Each of the minimization operators, in addition to
Topics
complexity boundscurvatureshapevariational methods
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@inproceedings{dudek1991shape, author = {Gregory Dudek}, title = {Shape Metrics From Curvature Scale-Space and Curvature-Tuned Smoothing}, booktitle = {Proceedings of the Conference on Geometric Methods in Computer Vision}, address = {San Diego, CA}, month = {July}, year = {1991} }

The Simulation of Sonar Mapping in Complex Environments Using Multiple Reflecting Surfaces

Michael Jenkin; Evangelos Milios; David Wilkes; Gregory Dudek

1991Proceedings of Vision Interface '91

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@inproceedings{jenkin1991simulation,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {The Simulation of Sonar Mapping in Complex Environments Using Multiple Reflecting Surfaces},
  booktitle = {Proceedings of Vision Interface '91},
  year      = {1991},
  pages     = {213--217},
  address   = {Calgary, Alta.},
  month     = {July}
}

Goal-directed Smoothing for the Curvature-based Segmentation of 3-Dimensional Surfaces
Tsotsos, John K.; Dudek, Gregory

1990Proceedings of the Canadian Society for the Computational Studies of Intelligence
Abstract
Abstract
Gregory Dudek Goal-directed smoothing for the curvature-based segmentation of 3-dimensional surfaces Pages 253–257
Topics
3d reconstructioncomplexity boundscurvaturegraph theoryshapevariational methods
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@inproceedings{tsotsos1990goal, title={Goal-directed Smoothing for the Curvature-based Segmentation of 3-Dimensional Surfaces}, author={Tsotsos, John K. and Dudek, Gregory}, booktitle={Proceedings of the Canadian Society for the Computational Studies of Intelligence}, pages={253--257}, year={1990}, address={Ottawa, Ontario}, month={May} }
Object Description Using Qualitative Surface Descriptors
Gregory Dudek

1990Proceedings of the AAAI-90 Workshop on Qualitative Vision
Abstract
Abstract
Object Description Using Qualitative Surface Descriptors
Topics
curvatureobject recognitionshapevariational methods
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@inproceedings{dudek1990object, author = {Gregory Dudek}, title = {Object Description Using Qualitative Surface Descriptors}, booktitle = {Proceedings of the AAAI-90 Workshop on Qualitative Vision}, address = {Boston, MA}, month = {July}, year = {1990} }
Recognizing Planar Curves Using Curvature-Tuned Smoothing
Tsotsos, John K.; Dudek, Gregory

1990Proceedings of the 10th International Conference of Pattern Recognition
Abstract
Abstract
uses curvature information and tracks the derivative of curvature across scales to produce a syntactic description of curves. The In this paper the authors present a new technique for both the fact that explicit parts are extracted by both these approaches smoothing and decomposition of planar curves. This technique, is a very useful and appealing characteristic. Contour informadubbed “curvature-tuned smoothing” provides for robust rota-tion has traditionally been easier to extract from images than tion and translation
Topics
curvatureobject recognitionshapevariational methods
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@inproceedings{tsotsos1990recognizing, title={Recognizing Planar Curves Using Curvature-Tuned Smoothing}, author={Tsotsos, John K. and Dudek, Gregory}, booktitle={Proceedings of the 10th International Conference of Pattern Recognition}, pages={130--135}, year={1990}, month={June}, address={Atlantic City, N.J.} }

The Decomposition and Representation of Planar Curves

Tsotsos; John K.; Gregory Dudek

1990Proceedings of the Conference on Curves and Surfaces in Computer Vision and Graphics

Abstract

The Decomposition and Representation of Planar Curves

Topics

curvatureshape

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@inproceedings{tsotsos1990decomposition,
  author    = {John K. Tsotsos and Gregory Dudek},
  title     = {The Decomposition and Representation of Planar Curves},
  booktitle = {Proceedings of the Conference on Curves and Surfaces in Computer Vision and Graphics},
  year      = {1990},
  address   = {Santa Clara, CA},
  month     = {February}
}

The Robust Simulation of Sonar Mapping from Multiple Viewpoints

Jenkin, Michael; Milios, Evangelos; Wilkes, David; Dudek, Gregory

1990Proceedings of the International Society for Optical Engineering Symposium on Advances in Intelligent Robotics Systems: Conference on Mobile Robotics V

Abstract

The Robust Simulation of Sonar Mapping from Multiple Viewpoints

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@inproceedings{jenkin1990robust,
  title={The Robust Simulation of Sonar Mapping from Multiple Viewpoints},
  author={Jenkin, Michael and Milios, Evangelos and Wilkes, David and Dudek, Gregory},
  booktitle={Proceedings of the International Society for Optical Engineering Symposium on Advances in Intelligent Robotics Systems: Conference on Mobile Robotics V},
  pages={536--542},
  year={1990},
  address={Boston, MA},
  month={November}
}

Using a Marker to Map an Unknown Environment

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1989Proceedings Vision Interface '89

Abstract

Using a Marker to Map an Unknown Environment

Topics

complexity boundsgraph theorylocalizationslamunderwater robotics

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@inproceedings{jenkin1989using,
  author    = {Michael Jenkin and Evangelos Milios and David Wilkes and Gregory Dudek},
  title     = {Using a Marker to Map an Unknown Environment},
  booktitle = {Proceedings Vision Interface '89},
  year      = {1989},
  pages     = {143--150},
  address   = {London, Ontario},
  month     = {June}
}

Using Multiple Markers in Graph Exploration
Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1989Proceedings of the International Society for Optical Engineering Symposium on Advances in Intelligent Robotics Systems: Conference on Mobile Robotics
Abstract
Abstract
A fundamental problem in robotics is that of exploring an unknown environment. Most current approaches to exploration make use of a global distance metric that is used to relate past sensory experiences to local measurements. Rather than rely on such an assumption we consider the more general problem of exploration without a distance metric, as is typical of exploring using only visual information: we propose robot exploration as graph building. In earlier papers we have shown that it is not possible for a robot to successfully explore a
Topics
complexity boundsexploration strategieslocalizationslam
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@inproceedings{jenkin1989using, title={Using Multiple Markers in Graph Exploration}, author={Jenkin, Michael and Milios, Evangelos and Wilkes, David and Dudek, Gregory}, booktitle={Proceedings of the International Society for Optical Engineering Symposium on Advances in Intelligent Robotics Systems: Conference on Mobile Robotics}, pages={77--87}, year={1989}, address={Philadelphia, PA}, month={November} }

How to Make Friends With Number-Crunchers: Adding Single-User Array-Processor Slave environment to VAX UNIX

Michael Jenkin; Howard Marcus; Gregory Dudek

1986Proceedings of 1986 USENIX Conference

Abstract

How to Make Friends With Number-Crunchers: Adding Single-User Array-Processor Slave environment to VAX UNIX

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@inproceedings{jenkin1986make,
  author    = {Michael Jenkin and Howard Marcus and Gregory Dudek},
  title     = {How to Make Friends With Number-Crunchers: Adding Single-User Array-Processor Slave environment to VAX UNIX},
  booktitle = {Proceedings of 1986 USENIX Conference},
  year      = {1986},
  address   = {Atlanta, GA},
  month     = {June},
  pages     = {200--208}
}

Design of a Microcomputer-Based Central File Server

Hamacher V.; Carl; Gregory Dudek; Richard C. Holt

1985Proceedings of the CIPS Congress

Abstract

Design of a Microcomputer-Based Central File Server

Topics

telecommunications

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@inproceedings{hamacher1985design,
  title={Design of a Microcomputer-Based Central File Server},
  author={Hamacher, V. Carl and Dudek, Gregory and Holt, Richard C.},
  booktitle={Proceedings of the CIPS Congress},
  pages={176--182},
  year={1985},
  address={Montreal, Quebec},
  month={June}
}

An Overview of the Metropolitan Toronto Traffic Control Computer System

Swanston; Edward N.; Richardson; David B.; Campbell; Hugh; Gregory Dudek

1983Proceedings of the 1983 International Electrical and Electronics Conference

Abstract

An Overview of the Metropolitan Toronto Traffic Control Computer System

Topics

complexity bounds

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@inproceedings{swanston1983overview,
  author    = {Edward N. Swanston and David B. Richardson and Hugh Campbell and Gregory Dudek},
  title     = {An Overview of the Metropolitan Toronto Traffic Control Computer System},
  booktitle = {Proceedings of the 1983 International Electrical and Electronics Conference},
  year      = {1983},
  address   = {Toronto, Ontario},
  month     = {March},
  pages     = {202--208}
}

Robotic exploration as graph construction

Jenkin; Michael; Milios; Evangelos; Wilkes; David; Gregory Dudek

1978J. Comput., vol

Abstract

We address the problem of robotic exploration of a graphlike world, where no distance or orientation metric is assumed of the world. The robot is assumed to be able to autonomously traverse graph edges, recognize when it has reached a vertex, and enumerate edges incident upon the current vertex relative to the edge via which it entered the current vertex. The robot cannot measure distances, and it does not have a compass. We demonstrate that this exploration problem is unsolvable in general without markers, and, to solve it, we equip

Topics

complexity boundslocalizationslam

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@article{dudek1978robotic,
 abstract = {We address the problem of robotic exploration of a graphlike world, where no distance or orientation metric is assumed of the world. The robot is assumed to be able to autonomously traverse graph edges, recognize when it has reached a vertex, and enumerate edges incident upon the current vertex relative to the edge via which it entered the current vertex. The robot cannot measure distances, and it does not have a compass. We demonstrate that this exploration problem is unsolvable in general without markers, and, to solve it, we equip},
 author = {Dudek, Gregory and Jenkin, Michael and Milios, Evangelos and Wilkes, David},
 journal = {J. Comput., vol},
 number = {3},
 pub_year = {1978},
 title = {Robotic exploration as graph construction},
 venue = {J. Comput., vol},
 volume = {7}
}

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On the Coverage of Planar Worlds with Simulated Mobile Ad Hoc Networks

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Learning heuristics for transit network design and improvement with deep reinforcement learning

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Swarm Oracle: Trustless Blockchain Agreements through Robot Swarms

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Computational Principles of Mobile Robotics (3rd edition)

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Device-Free Human State Estimation Using UWB Multi-Static Radios

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Reference-Guided Robotic Photography Through Natural Language Interaction

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