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
相关论文
共 50 条
  • [31] Coverage path planning of unmanned surface vehicle based on improved biological inspired neural network
    Tang, Fei
    OCEAN ENGINEERING, 2023, 278
  • [32] An Algorithm for Path Planning of Multiple Unmanned Aerial Vehicles Based on Bezier Curve
    Hu Feng
    Wang Shuo
    PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE, 2010, : 3660 - 3665
  • [33] Path Planning of an Unmanned Surface Vessel Based on the Improved A-Star and Dynamic Window Method
    Hu, Shunan
    Tian, Shenpeng
    Zhao, Jiansen
    Shen, Ruiqi
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (05)
  • [34] A Path Planning Method for Sweep Coverage With Multiple UAVs
    Li, Jing
    Xiong, Yonghua
    She, Jinhua
    Wu, Min
    IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (09) : 8967 - 8978
  • [35] A path planning approach for unmanned surface vehicles based on dynamic and fast Q-learning
    Hao, Bing
    Du, He
    Yan, Zheping
    OCEAN ENGINEERING, 2023, 270
  • [36] Coverage Path Planning Method of Unmanned Aerial Vehicle for Aircraft Surface Detection Task
    Dai J.
    Gong X.
    Wang J.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2023, 59 (16): : 243 - 253
  • [37] Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization
    Na, Yiwei
    Li, Yulong
    Chen, Danqiang
    Yao, Yongming
    Li, Tianyu
    Liu, Huiying
    Wang, Kuankuan
    SUSTAINABILITY, 2023, 15 (16)
  • [38] <bold>A Green Ant-based method for Path Planning of Unmanned Ground Vehicles </bold>
    Jabbarpour, Mohanmmad Rzea
    Zarrabi, Houman
    Jung, Jason J.
    Kim, Pankoo
    IEEE ACCESS, 2017, 5 : 1820 - 1832
  • [39] Parallel Algorithm for the Path Planning of Multiple Unmanned Aerial Vehicles
    Roberge, Vincent
    Tarbouchi, Mohammed
    2020 FOURTH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING IN DATA SCIENCES (ICDS), 2020,
  • [40] A novel path planning method for wheel-legged unmanned vehicles based on improved ant colony algorithm
    Zhao, Jing
    Li, Hongcai
    Yang, Chao
    Wang, Weida
    2021 60TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE), 2021, : 696 - 701