Gaussian Sampling for Probabilistic Roadmap Planners
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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, sample sampling strategy, which we call the Gaussian sampler, that gives a much better coverage of the dificult parts of the free Configuration...
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A probabilistic roadmap is a network of simple paths connecting collision-free conngurations obtained by sampling a robot's connguration space at random. Several probabilistic roadmap planners have solved unusually diicult path-planning problems, but their ee-ciency remains disappointing when the free space contains narrow passages. This paper provides foundations for understanding the eeect of...
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