TY - GEN
T1 - Distributed multi-robot motion planning for cooperative multi-area coverage
AU - Xin, Bin
AU - Gao, Guan Qiang
AU - Ding, Yu Long
AU - Zhu, Yang Guang
AU - Fang, Hao
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/4
Y1 - 2017/8/4
N2 - The Cooperative Multi-Area Coverage (CMAC) refers to a class of complex tasks in which multiple robots are required to jointly cover multiple areas by performing specific operations while moving across them. Practical operations may be garbage clearance, demining, area scanning for information acquisition, and so on. This paper proposes a distributed motion planning method for multiple robots to cooperatively accomplish CMAC tasks. Firstly, a general multi-robot task model recently proposed, named multi-point dynamic aggregation (MPDA), is applied to formulate the multi-robot motion planning problem in CMAC. Then, a rule-based heuristic for the distributed motion planning of each single robot is set forth. Further, coordination mechanisms are proposed to coordinate multiple robots from the perspective of both task allocation and motion planning. Simulations validate the effectiveness of the proposed distributed motion planning method.
AB - The Cooperative Multi-Area Coverage (CMAC) refers to a class of complex tasks in which multiple robots are required to jointly cover multiple areas by performing specific operations while moving across them. Practical operations may be garbage clearance, demining, area scanning for information acquisition, and so on. This paper proposes a distributed motion planning method for multiple robots to cooperatively accomplish CMAC tasks. Firstly, a general multi-robot task model recently proposed, named multi-point dynamic aggregation (MPDA), is applied to formulate the multi-robot motion planning problem in CMAC. Then, a rule-based heuristic for the distributed motion planning of each single robot is set forth. Further, coordination mechanisms are proposed to coordinate multiple robots from the perspective of both task allocation and motion planning. Simulations validate the effectiveness of the proposed distributed motion planning method.
UR - http://www.scopus.com/inward/record.url?scp=85029906798&partnerID=8YFLogxK
U2 - 10.1109/ICCA.2017.8003087
DO - 10.1109/ICCA.2017.8003087
M3 - Conference contribution
AN - SCOPUS:85029906798
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 361
EP - 366
BT - 2017 13th IEEE International Conference on Control and Automation, ICCA 2017
PB - IEEE Computer Society
T2 - 13th IEEE International Conference on Control and Automation, ICCA 2017
Y2 - 3 July 2017 through 6 July 2017
ER -
