Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
Particle Filters In Robotics
Sebastian Thrun
Carnegie Mellon University
Monday, September 30, 2002, 4:15PM
TCseq 200
http://robotics.stanford.edu/ba-colloquium/
Abstract
This presentation will introduce the audience to an emerging body
of research on sequential markov chain monte carlo techniques in
robotics. In recent years, particle filters have solved several hard
robotic problems. Early successes were limited to low-dimensional
problems, such as the problem of robot localization in environments
with known maps. More recently, we have begun to exploit structural
properties of robotic domains, to scale particle filters to spaces with
as many as 100,000 dimensions. The presentation will discuss specific
`tricks' necessary to make these statistical techniques work in robotics,
and present robot systems that use particle filters for real-world
perception.
Joint work with Michael Montemerlo (CMU), Daphne Koller and
Ben Wegbreit (Stanford), and Juan Nieto and Eduardo Nebot
(Univ. of Sydney).
About the Speaker
Sebastian Thrun is the Finmeccanica Associate Professor of Computer
Science and Robotics at Carnegie Mellon University. His interests lie in
the areas of robotics, computational machine learning, and human robot
interaction.
Contact: bac-coordinators@cs.stanford.edu
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