Our paper "Generating adversarial driving scenarios in high-fidelity simulators", looks at using
adversarial methods to allow autonomous driving agents to improve.
The paper was an
early example of the developing trend to develop more robust agents
by making the environment part of the learning cycyle.
Searching for novelty is video, and using it to navigate a swimming robot to maximize the
stuff that is observed. Autonomous
Adaptive Underwater Exploration using Online Topic Modeling with Yogesh my student and Philippe (from Laval University).
This combines an automated search for novelty with the behavior of our amphibious robot. A journal version can
also be found in the Intl Journal of Robotics Research in 2013.
interaction (HRI) and dialog
is a key aspect of robotics and the student author (Junead) is now professor at the University of Minnesota. This 2011 paper
is an eraly step in validating HRI methods.
Work on using visual landmarks for pose estimation.
We have look at several variants of this and the following
CVPR 2001 paper (postscript, gz)
uses generative models.
Initial work on reconstruction of depth images from intensity data
with Luz-Abril Torres Mendez, from
the proc. IEEE Workshop of Applications of Computer Vision 2002
(PDF file). (Starting paper, see
papers for better results.)
for Multi-Agent Robotics. Combines a taxonomy, some new results,
and a survey of existing work. A preprint of this article can
be found as a PDF file (an older journal article that was retreaded and
updated for the book Robot Teams: From Diversity to Polymorphism, T. Balch and
L. E. Parker (Eds.), 2002).