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


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.

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