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The Gaussian sampling strategy for probabilistic roadmap planners

Boor, V., Overmars, M.H., van der Stappen, A.F.·2003·Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)

Abstract

Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to sample the free configuration space. In this paper we present a new, simple sampling strategy, which we call the Gaussian sampler, that gives a much better coverage of the difficult parts of the free configuration space. The approach uses only elementary operations which makes it suitable for many different planning problems. Experiments indicate that the technique is very efficient indeed.

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Metadata

Authors
Boor, V., Overmars, M. H., & van der Stappen, A. F.
Venue
Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
Publisher
IEEE
Published
2003-01-20
Volume
2
Pages
1018-1023
ISSN
1050-4729 (ISSN-L)
OpenAlex
W2107535513
Cited by
541
References
1
FWCI
26.90
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Gaussian sampling strategy for probabilistic roadmap planners. https://app.cochat.ai/papers/10.1109/robot.1999.772447
The paper
Boor, V., Overmars, M. H., & van der Stappen, A. F. (2003). The Gaussian sampling strategy for probabilistic roadmap planners. Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C). https://doi.org/10.1109/robot.1999.772447

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