UOBPRM: A uniformly distributed obstacle-based PRM

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2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, ISSN: 2153-0858, Page: 2655-2662

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http://scholars.library.tamu.edu/vivo/display/n60456SE; http://hdl.handle.net/10754/600140
Yeh, Hsin-Yi; Thomas, Shawna; Eppstein, David; Amato, Nancy M.
Institute of Electrical and Electronics Engineers (IEEE)
Engineering; Computer Science
conference paper description
This paper presents a new sampling method for motion planning that can generate configurations more uniformly distributed on C-obstacle surfaces than prior approaches. Here, roadmap nodes are generated from the intersections between C-obstacles and a set of uniformly distributed fixed-length segments in C-space. The results show that this new sampling method yields samples that are more uniformly distributed than previous obstacle-based methods such as OBPRM, Gaussian sampling, and Bridge test sampling. UOBPRM is shown to have nodes more uniformly distributed near C-obstacle surfaces and also requires the fewest nodes and edges to solve challenging motion planning problems with varying narrow passages. © 2012 IEEE.