Uncertainty in Artificial Intelligence
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Particle Filters in Robotics (Invited Talk)
Sebastian Thrun
Abstract:
This presentation will introduce the audience to a new, emerging body of research on sequential Monte Carlo techniques in robotics. In recent years, particle filters have solved several hard perceptual robotic problems. Early successes were limited to low-dimensional problems, such as the problem of robot localization in environments with known maps. More recently, researchers have begun exploiting structural properties of robotic domains that have led to successful particle filter applications in spaces with as many as 100,000 dimensions. The presentation will discuss specific tricks necessary to make these techniques work in real - world domains,and also discuss open challenges for researchers IN the UAI community.
Keywords:
Pages: 511-518
PS Link:
PDF Link: /papers/02/p511-thrun.pdf
BibTex:
@INPROCEEDINGS{Thrun02,
AUTHOR = "Sebastian Thrun ",
TITLE = "Particle Filters in Robotics (Invited Talk)",
BOOKTITLE = "Proceedings of the Eighteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-02)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2002",
PAGES = "511--518"
}


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