UOBPRM: A uniformly distributed obstacle-based PRM Conference Paper uri icon

abstract

  • 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.

name of conference

  • 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012)

published proceedings

  • 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

author list (cited authors)

  • Yeh, H., Thomas, S., Eppstein, D., & Amato, N. M

citation count

  • 28

complete list of authors

  • Yeh, Hsin-Yi||Thomas, Shawna||Eppstein, David||Amato, Nancy M

publication date

  • October 2012

publisher