The Gaussian sampling strategy for probabilistic roadmap planners

The Gaussian sampling strategy for probabilistic roadmap planners

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 Ga...

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Bibliographic Details
Published in:Proceedings - IEEE International Conference on Robotics and Automation Vol. 2; pp. 1018 - 1023 vol.2
Main Authors: Boor, V., Overmars, M.H., van der Stappen, A.F.
Format: Conference Proceeding Journal Article
Language:English
Published: IEEE 1999
Subjects:
Computer science
Genetic algorithms
Layout
Mobile robots
Motion planning
Neural networks
Orbital robotics
Path planning
Sampling methods
Online Access:Get full text
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Summary: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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ISBN:9780780351806
0780351800
ISSN:1050-4729
2577-087X
DOI:10.1109/ROBOT.1999.772447