A global path planning method for mobile docking AUV

被引：0
作者：
Zhu, Zijian [1 ,2 ]
Jiang, Yanqing [1 ,2 ,3 ]
Li, Keyao [1 ,2 ]
Sun, Weijie [3 ]
Li, Shuchang [1 ,2 ]
Xu, Jianxin [1 ,2 ]
Zhang, Wenjun [1 ,2 ]
Wu, Haowei [4 ]
机构：
[1] Key Laboratory of Underwater Intelligent Robot Technology, Harbin Engineering University, Harbin
[2] College of Shipbuilding Engineering, Harbin Engineering University, Harbin
[3] Sanya Nanhai Innovation & Development Center, Harbin Engineering University, Sanya
[4] China Academy of Launch Vehicle Technology, Beijing
来源：
Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2024年 / 45卷 / 10期
关键词：
artificial potential field method; global prediction; mobile docking; path planning; recovery; state constraints; state estimation; underactuated autonomous underwater vehicle;
D O I：
10.11990/jheu.202303004
中图分类号：
学科分类号：
摘要：
In view of the multiple geometric constraints on the global path caused by the autonomous underwater vehicle (AUV)under-actuation control characteristics when the AUV and the mother ship are dynamically docked, as well as the dynamic changes of the terminal constraints of the path caused by the dynamic changes of the intersection points caused by the mother ship movement, this paper proposes an autonomous docking path planning method for the AUV. The proposed method is mainly divided into three parts: constraint solving, motion planning and state estimation. Firstly, the motion constraints and terminal constraints in the docking process are analyzed using the AUV dynamics model; On the premise of motion constraints and terminal constraints, the global path planning algorithms under position constraints and attitude constraints are designed based on the idea of potential field method. At the same time, the position, speed and attitude estimation methods of the mother ship are proposed, and the simulation of the path planning method based on global prediction is carried out accordingly. The simulation results show that the method in this paper has fast operation speed, good robustness to the state of the mother ship, and meets the motion constraints and terminal constraints. It can obtain a path planning algorithm that satisfies the constraint conditions of a smooth path when testing and simulating the homing of a real AUV. © 2024 Editorial Board of Journal of Harbin Engineering. All rights reserved.
引用
收藏
页码：1873 / 1879
页数：6
相关论文
共 16 条
  • [1] HUANG Yan, LI Yan, YU Jiancheng, Et al., Present situation and development trend of AUV intelligence, Robot, 42, 2, pp. 215-231, (2020)
  • [2] REN Ye, WANG Junxiong, ZHANG Xiaoqing, Research on path planning of AUV based on multi-factor improved A<sup>∗</sup> algorithm, Ship science and technology, 44, 11, pp. 58-62, (2022)
  • [3] CHE Gaofeng, LIU Lijun, YU Zhen, An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle, Journal of ambient intelligence and humanized computing, 11, 8, pp. 3349-3354, (2020)
  • [4] HUANG Haoqian, JIN Chao, A novel particle swarm optimization algorithm based on reinforcement learning mechanism for AUV path planning [ J ], Complexity, 2021, (2021)
  • [5] GU Guochang, FU Yan, LIU Haibo, Path planning of underwater vehicle based on genetic simulated annealing algorithm, Journal of Harbin Engineering University, 26, 1, pp. 84-87, (2005)
  • [6] LI Shuai, GUO Yi, Neural-network based AUV path planning in estuary environments, Proceedings of the 10th World Congress on Intelligent Control and Automation, pp. 3724-3730, (2012)
  • [7] YAO Peng, WEI Xin, QIU Liyan, Et al., AUV path planning for target search using bioinspired neural network, 2020 3rd International Conference on Unmanned Systems (ICUS), pp. 575-580, (2020)
  • [8] FAN Xiaojing, GUO Yinjing, LIU Hui, Et al., Improved artificial potential field method applied for AUV path planning, Mathematical problems in engineering, 2020, (2020)
  • [9] LAI T H, LEE D., A path planning algorithm for AUV using fuzzy logic and artificial potential field, Journal of institute of control, robotics and systems, 28, 6, pp. 589-595, (2022)
  • [10] LI Ye, JIA Zhihao, ZHANG Weibin, Et al., Hierarchical trajectory planning and test for autonomous berthing of unmanned boats, Journal of Harbin Engineering University, 40, 6, pp. 1043-1050, (2019)
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