On the probabilistic completeness of the sampling-based feedback motion planners in belief space

Ali Akbar Agha-Mohammadi, Suman Chakravorty, Nancy M. Amato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper extends the concept of "probabilistic completeness" defined for motion planners in state space (or configuration space) to the concept of "probabilistic completeness under uncertainty" for motion planners in belief space. Accordingly, an approach is proposed to verify the probabilistic completeness of the sampling-based planners in belief space. Finally, through the proposed approach, it is shown that under mild conditions the sampling-based methods constructed based on the abstract framework of FIRM (Feedback-based Information Roadmap Method) are probabilistically complete under uncertainty.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3983-3990
Number of pages8
ISBN (Print)9781467314039
DOIs
StatePublished - 2012
Externally publishedYes
Event 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 - Saint Paul, MN, United States
Duration: May 14 2012May 18 2012

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
Country/TerritoryUnited States
CitySaint Paul, MN
Period5/14/125/18/12

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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