Probabilistic collision state checker for crowded environments

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...

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Bibliographic Details
Published in2010 IEEE International Conference on Robotics and Automation pp. 1492 - 1498
Main Authors Althoff, Daniel, Althoff, Matthias, Wollherr, Dirk, Buss, Martin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2010
Subjects
Collision mitigation
Humans
Path planning
Personal communication networks
Robotics and automation
Robots
State estimation
USA Councils
Vehicle detection
Vehicle safety
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ISBN9781424450381
1424450381
ISSN1050-4729
DOI10.1109/ROBOT.2010.5509369

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Summary: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.
ISBN:9781424450381
1424450381
ISSN:1050-4729
DOI:10.1109/ROBOT.2010.5509369