Probabilistic collision state checker for crowded environments

Daniel Althoff, Matthias Althoff, Dirk Wollherr, Martin Buss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

39 Scopus citations

Abstract

For path planning algorithms of robots it is important that the robot does not reach a state of inevitable collision. In crowded environments with many humans or robots, the set of possible inevitable collision states (ICS) is often unacceptably high, such that the robot has to stop and wait in too many situations. For this reason, the concept of ICS is extended to probabilistic collision states (PCS), which estimates the collision probability for a given state. This allows to efficiently run planning algorithms through crowded environments when accepting a certain collision probability. A further novelty is that the obstacles possibly react to the robot in order to mitigate the risk of a collision. The results show a significant difference in interaction behavior. Thus, this approach is especially suited for active and non-deterministic moving obstacles in the robot workspace.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Pages1492-1498
Number of pages7
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
Duration: 3 May 20107 May 2010

Publication series

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

Conference

Conference2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Country/TerritoryUnited States
CityAnchorage, AK
Period3/05/107/05/10

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