Probably approximately correct coverage for robots with uncertainty

Colin Das, Aaron Becker, Timothy Bretl

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

Abstract

The classical problem of robot coverage is to plan a path that brings a point on the robot within a fixed distance of every point in the free space. In the presence of significant uncertainty in sensing and actuation, it may no longer be possible to guarantee that the robot covers all of the free space all the time, and so it becomes unclear what problem we are trying to solve. We will restore clarity by adopting a "probably approximately correct" measure of performance that captures the probability 1-ε of covering a fraction 1-δ of the free space. The problem of coverage for a robot with uncertainty is then to plan a feedback policy that achieves a given value of ε and δ. Just as solutions to the classical problem are judged by the resulting path length, solutions to our problem are judged by the required execution time. We will show the practical utility of our performance measure by applying it to several examples in simulation.

Original languageEnglish (US)
Title of host publicationIROS'11 - 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Subtitle of host publicationCelebrating 50 Years of Robotics
Pages1160-1166
Number of pages7
DOIs
StatePublished - Dec 29 2011
Event2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11 - San Francisco, CA, United States
Duration: Sep 25 2011Sep 30 2011

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Other

Other2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11
CountryUnited States
CitySan Francisco, CA
Period9/25/119/30/11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Probably approximately correct coverage for robots with uncertainty'. Together they form a unique fingerprint.

Cite this