Efficient Path Following Algorithm for Unmanned Surface Vehicle

被引:0
|
作者
Niu, Hanlin [1 ]
Lu, Yu [1 ]
Savvaris, Al [1 ]
Tsourdos, Antonios [1 ]
机构
[1] Cranfield Univ, Sch Aerosp Transport & Mfg, Bedford, England
来源
关键词
Unmanned marine vehicles; Long endurance; Path following; Marine system navigation; guidance and control; GENERATION;
D O I
暂无
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
This paper presents the comparison and analysis of four common path following algorithms for the C-Enduro unmanned surface vehicle (USV), which is designed to operate at sea for extended periods of time (up to 3 months). Four path following algorithms were tested that include Carrot chasing path following, Nonlinear guidance law, Pure pursuit and line-of-sight (PLOS) path following and Vector field algorithms. The simulation was realized by implementing the 3 DOF dynamic model of C-Enduro USV. The simulation also took account of the environmental factors, i.e., wind and current. The accuracy and control effort of these four algorithms are compared and analyzed. The simulation results can be used to assist in deciding which path following algorithm the USV needs to implement in order to deal with different missions efficiently.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Dynamic Path Planning Algorithm for Unmanned Surface Vehicle Under Island-Reef Environment
    Zhang, Jing
    Cui, Yani
    Li, Guangfu
    Ren, Jia
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2023, 59 (05) : 7252 - 7268
  • [42] Dynamic path planning for unmanned surface vehicle in complex offshore areas based on hybrid algorithm
    Wang, Zheng
    Li, Guangfu
    Ren, Jia
    [J]. COMPUTER COMMUNICATIONS, 2021, 166 : 49 - 56
  • [43] An enhanced path planning method for unmanned surface vehicle based on JPS plus and goalbounding algorithm
    Xu, Xiaoqiang
    Li, Xiaohan
    Zhan, Ao
    [J]. 2019 INTERNATIONAL CONFERENCE ON ADVANCED ELECTRONIC MATERIALS, COMPUTERS AND MATERIALS ENGINEERING (AEMCME 2019), 2019, 563
  • [44] Energy efficient path planning for Unmanned Surface Vehicle in spatially-temporally variant environment
    Niu, Hanlin
    Ji, Ze
    Al Savvaris
    Tsourdos, Antonios
    [J]. OCEAN ENGINEERING, 2020, 196
  • [45] A 3D-Sparse A* autonomous recovery path planning algorithm for Unmanned Surface Vehicle
    Zhou, Lulu
    Ye, Xiaoming
    Yang, Xianyong
    Shao, Yong
    Liu, Xiang
    Xie, Pengzhan
    Tong, Yanjia
    [J]. OCEAN ENGINEERING, 2024, 301
  • [46] Global Path Planning for Unmanned Surface Vehicle Based on Improved Quantum Ant Colony Algorithm
    Xia, Guoqing
    Han, Zhiwei
    Zhao, Bo
    Liu, Caiyun
    Wang, Xinwei
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2019, 2019
  • [47] Maritime Search Path Planning Method of an Unmanned Surface Vehicle Based on an Improved Bug Algorithm
    Wang, Xiuling
    Yin, Yong
    Jing, Qianfeng
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (12)
  • [48] DEMRL: Dynamic estimation meta reinforcement learning for path following on unseen unmanned surface vehicle
    Jin, Kefan
    Zhu, Hao
    Gao, Rui
    Wang, Jian
    Wang, Hongdong
    Yi, Hong
    Shi, C. -J. Richard
    [J]. OCEAN ENGINEERING, 2023, 288
  • [49] An Energy-saving Control Method for Path Following of An Unmanned Surface Vehicle in Wave Field
    Zhang, Shanjia
    Wang, Jianhua
    Wen, Xiangxin
    Zhao, Minghui
    Zhang, Cheng
    Cong, Xiaoyi
    [J]. 2018 INTERNATIONAL SYMPOSIUM IN SENSING AND INSTRUMENTATION IN IOT ERA (ISSI), 2018,
  • [50] An energy-efficient hierarchical algorithm of dynamic obstacle avoidance for unmanned surface vehicle
    Wang, Jiaqi
    Li, Shixin
    Li, Boyang
    Zhao, Chenyu
    Cui, Ying
    [J]. INTERNATIONAL JOURNAL OF NAVAL ARCHITECTURE AND OCEAN ENGINEERING, 2023, 15