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Mobile Robot Localisation Using
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ACKNOWLEDGEMENTS
Contents
List of Figures
Introduction
Problem Statement
Approach
Applications
Outline
Previous Work
Triangulation Methods
Kalman Filtering
Feature-Based Methods
Sensor Inversion
Visual Attention
Learning Landmarks
Edge Detection
Feature Interpretation
Landmark Detection
Visual Tracking
Landmark Recognition
Landmark Tracking
Example: A Small Database
Position Estimation
Estimation by Linear Combination
Robust Estimate Combination
Estimating Error
Removing Outliers
Experimental Results
A Simple Scene
Parameter Variation
Appearance-only Pose Estimates
Using the Edge Distribution
A Larger Scene
Two Indoor Scenes
A Laboratory Environment
Laboratory Environment Revisited
Recovering Orientation
Discussion and Conclusions
Overview
Landmarks
Pose Estimation
Experimental Results
Future Work
Visual Attention
Visual Tracking
Parameterisation Properties
Conclusion
References
About this document ...
Robert Sim
Tue Jul 21 10:30:54 EDT 1998