Adaptive and relaxed visibility-based PRM

Tian-Ming Bu*, Zhen-Jian Li, Zheng Sun

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)


In this paper we introduce a new sampler for robotic motion planning using the probabilistic roadmap approach. We improve the previously-introduced visibility-based sampler with two heuristics. First, we adopt a space decomposition approach can guide the sampler by identifying promising areas of the configuration space where milestones can be efficiently generated. While the original visibility-based sampler uses a very selective criterion to determine whether a sampled configuration point is to be accepted as a new milestone, we use a relaxed criterion that can significantly reduce the computational cost in the roadmap construction phase while increasing the size of the roadmap only mildly.

Original languageEnglish
Title of host publication2005 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO
Number of pages6
ISBN (Print)0780393155, 9780780393158
Publication statusPublished - 5 Jul 2005
Externally publishedYes
EventIEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2005 - , Hong Kong
Duration: 5 Jul 20059 Jul 2005

Publication series

NameIEEE International Conference on Robotics and Biomimetics


ConferenceIEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2005
Country/TerritoryHong Kong
Internet address

Scopus Subject Areas

  • Engineering(all)


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