TY - GEN
T1 - Bipartite graph matching-based coordination mechanism for multi-robot path planning under communication constraints
AU - Dutta, Ayan
AU - Dasgupta, Prithviraj
PY - 2017/7/21
Y1 - 2017/7/21
N2 - We propose a coordination mechanism to avoid inter-robot collisions when the robots' paths overlap with each other. Our proposed coordination technique uses a weighted bipartite matching-based formulation to solve this problem. Initially, each robot is given a unique goal location. But the robots do not know about other robots' planned paths until they come within each other's communication ranges. When two or more robots get within an unsafe distance, they coordinate their paths to avoid collisions with each other. The objective of the coordination mechanism is to plan a modified path for each coordinating robot (if needed) so that all the robots can reach their goal locations without collision with each other and also while reducing the extra distance introduced while resolving path conflicts. We have proved the correctness and convergence of our coordination strategy. Our experimental results show that the robots using our proposed strategy travel up to 4.2 times less than a comparable heuristic approach.
AB - We propose a coordination mechanism to avoid inter-robot collisions when the robots' paths overlap with each other. Our proposed coordination technique uses a weighted bipartite matching-based formulation to solve this problem. Initially, each robot is given a unique goal location. But the robots do not know about other robots' planned paths until they come within each other's communication ranges. When two or more robots get within an unsafe distance, they coordinate their paths to avoid collisions with each other. The objective of the coordination mechanism is to plan a modified path for each coordinating robot (if needed) so that all the robots can reach their goal locations without collision with each other and also while reducing the extra distance introduced while resolving path conflicts. We have proved the correctness and convergence of our coordination strategy. Our experimental results show that the robots using our proposed strategy travel up to 4.2 times less than a comparable heuristic approach.
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U2 - 10.1109/ICRA.2017.7989105
DO - 10.1109/ICRA.2017.7989105
M3 - Conference contribution
AN - SCOPUS:85027995952
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 857
EP - 862
BT - ICRA 2017 - IEEE International Conference on Robotics and Automation
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Robotics and Automation, ICRA 2017
Y2 - 29 May 2017 through 3 June 2017
ER -