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ICRA
2005
IEEE

Hybrid PRM Sampling with a Cost-Sensitive Adaptive Strategy

10 years 3 months ago
Hybrid PRM Sampling with a Cost-Sensitive Adaptive Strategy
— A number of advanced sampling strategies have been proposed in recent years to address the narrow passage problem for probabilistic roadmap (PRM) planning. These sampling strategies all have unique strengths, but none of them solves the problem completely. In this paper, we present a general and systematic approach for adaptively combining multiple sampling strategies so that their individual strengths are preserved. We have performed experiments with this approach on robots with up to 12 degrees of freedom in complex 3-D environments. Experiments show that although the performance of individual sampling strategies varies across different environments, the adaptive hybrid sampling strategies constructed with this approach perform consistently well in all environments. Further, we show that, under reasonable assumptions, the adaptive strategies are provably competitive against all individual strategies used.
David Hsu, Gildardo Sánchez-Ante, Zheng Sun
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ICRA
Authors David Hsu, Gildardo Sánchez-Ante, Zheng Sun
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