CCIBA*: An Improved BA* Based Collaborative Coverage Path Planning Method for Multiple Unmanned Surface Mapping Vehicles

被引:29
|
作者
Ma, Yong [1 ,2 ,3 ]
Zhao, Yujiao [1 ,2 ,3 ]
Li, Zhixiong [4 ,5 ]
Bi, Huaxiong [1 ,2 ,3 ]
Wang, Jing [1 ,2 ,3 ]
Malekian, Reza [6 ]
Sotelo, Miguel Angel [7 ]
机构
[1] Wuhan Univ Technol, Sch Nav, Hubei Key Lab Inland Shipping Technol, Wuhan 430063, Peoples R China
[2] Wuhan Univ Technol, Sanya Sci & Educ Innovat Pk, Wuhan 572000, Peoples R China
[3] Wuhan Univ Technol, Chongqing Res Inst, Chongqing 401120, Peoples R China
[4] Opole Univ Technol, Fac Mech Engn, PL-45758 Opole, Poland
[5] Yonsei Univ, Yonsei Frontier Lab, Seoul 03722, South Korea
[6] Malmo Univ, Dept Comp Sci & Media Technol, S-20506 Malmo, Sweden
[7] Univ Alcala, Dept Comp Engn, Alcala De Henares 28801, Spain
基金
美国国家科学基金会;
关键词
Path planning; Task analysis; Collaboration; Heuristic algorithms; Behavioral sciences; Robots; Potential energy; Multiple USMVs; collaborative coverage; path planning; CCIBA*; task decomposition; ANT COLONY OPTIMIZATION; ALGORITHM; NAVIGATION; NETWORK;
D O I
10.1109/TITS.2022.3170322
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The main emphasis of this work is placed on the problem of collaborative coverage path planning for unmanned surface mapping vehicles (USMVs). As a result, the collaborative coverage improved BA* algorithm (CCIBA*) is proposed. In the algorithm, coverage path planning for a single vehicle is achieved by task decomposition and level map updating. Then a multiple USMV collaborative behavior strategy is designed, which is composed of area division, recall and transfer, area exchange and recognizing obstacles. Moverover, multiple USMV collaborative coverage path planning can be achieved. Consequently, a high-efficiency and high-quality coverage path for USMVs can be implemented. Water area simulation results indicate that our CCIBA* brings about a substantial increase in the performances of path length, number of turning, number of units and coverage rate.
引用
收藏
页码:19578 / 19588
页数:11
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