Title :
Probabilistic collision state checker for crowded environments
Author :
Althoff, Daniel ; Althoff, Matthias ; Wollherr, Dirk ; Buss, Martin
Author_Institution :
Inst. of Autom. Control Eng., (LSR), Tech. Univ. Munchen, München, Germany
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.
Keywords :
collision avoidance; mobile robots; probability; crowded environments; inevitable collision states; path planning algorithms; probabilistic collision state checker; robots; Collision mitigation; Humans; Path planning; Personal communication networks; Robotics and automation; Robots; State estimation; USA Councils; Vehicle detection; Vehicle safety;
Conference_Titel :
Robotics and Automation (ICRA), 2010 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-5038-1
Electronic_ISBN :
1050-4729
DOI :
10.1109/ROBOT.2010.5509369