Distributed Optimization-Based Path Planning for Multiple Unmanned Surface Vehicles to Pass through Narrow Waters

被引:0
作者
Li, Shuo [1 ]
Teng, Fei [1 ]
Xiao, Geyang [2 ]
Zhao, Haoran [3 ]
机构
[1] Dalian Maritime Univ, Marine Elect Engn Coll, Dalian 116026, Peoples R China
[2] Zhejiang Lab, Res Inst Intelligent Networks, Hangzhou 311121, Peoples R China
[3] Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China
基金
中国国家自然科学基金;
关键词
multi-unmanned surface vehicle system; path planning; distributed optimization algorithm; polymorphic network;
D O I
10.3390/jmse12081246
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Safety and efficiency are important when Unmanned Surface Vehicles (USVs) pass through narrow waters in complex marine environments. This paper considers the issue of path planning for USVs passing through narrow waterways. We propose a distributed optimization algorithm based on a polymorphic network architecture, which maintains connectivity and avoids collisions between USVs while planning optimal paths. Firstly, the initial path through the narrow waterway is planned for each USV using the narrow water standard route method, and then the interpolating spline method is used to determine its corresponding functional form and rewrite the function as a local cost function for the USV. Secondly, a polymorphic network architecture and a distributed optimization algorithm were designed for multi-USVs to maintain connectivity and avoid collisions between USVs, and to optimize the initial paths of the multi-USV system. The effectiveness of the algorithm is demonstrated by Lyapunov stability analysis. Finally, Lingshui Harbor of Dalian Maritime University and a curved narrow waterway were selected for the simulation experiments, and the results demonstrate that the paths planned by multiple USVs were optimal and collision-free, with velocities achieving consistency within a finite time.
引用
收藏
页数:19
相关论文
共 42 条
  • [21] Scanning-Chain Formation Control for Multiple Unmanned Surface Vessels to Pass Through Water Channels
    Liu, Bin
    Zhang, Hai-Tao
    Meng, Haofei
    Fu, Dongfei
    Su, Housheng
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2022, 52 (03) : 1850 - 1861
  • [22] Motion planning for unmanned surface vehicle based on a maneuverability mathematical model
    Liu, Dong-yu
    Gao, Xiao-peng
    Huo, Cong
    [J]. OCEAN ENGINEERING, 2022, 265
  • [23] Trajectory planning for unmanned surface vehicles in multi-ship encounter situations
    Liu, Jianjian
    Chen, Huizi
    Xie, Shaorong
    Peng, Yan
    Zhang, Dan
    Pu, Huayan
    [J]. OCEAN ENGINEERING, 2023, 285
  • [24] Lu Yuzhou, 2023, 2023 International Conference on Ubiquitous Communication (Ucom), P455, DOI 10.1109/Ucom59132.2023.10257615
  • [25] Green Polymorphic Cooperative Formation Strategy of Low-Carbon Unmanned Surface Vessels
    Lu, Yuzhou
    Shan, Qihe
    Xiao, Geyang
    Liang, Yuan
    Liu, Wei
    [J]. FRONTIERS IN ENERGY RESEARCH, 2022, 10
  • [26] A collision avoidance approach via negotiation protocol for a swarm of USVs
    Ma, Yong
    Zhao, Yujiao
    Incecik, Atilla
    Yan, Xinping
    Wang, Yulong
    Li, Zhixiong
    [J]. OCEAN ENGINEERING, 2021, 224
  • [27] Collision-avoidance under COLREGS for unmanned surface vehicles via deep reinforcement learning
    Ma, Yong
    Zhao, Yujiao
    Wang, Yulong
    Gan, Langxiong
    Zheng, Yuanzhou
    [J]. MARITIME POLICY & MANAGEMENT, 2020, 47 (05) : 665 - 686
  • [28] Consensus problems in networks of agents with switching topology and time-delays
    Olfati-Saber, R
    Murray, RM
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2004, 49 (09) : 1520 - 1533
  • [29] Equilateral triangular formation of unmanned surface vehicles for target tracking with event-triggered collision avoidance
    Qian, Guohu
    Zheng, Xiang
    Wang, Jianhua
    Xie, Zhigang
    Wu, Qiwen
    Xu, Wei
    [J]. OCEAN ENGINEERING, 2023, 267
  • [30] Distributed Continuous-Time Convex Optimization With Time-Varying Cost Functions
    Rahili, Salar
    Ren, Wei
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2017, 62 (04) : 1590 - 1605