A survey of underwater search for multi-target using Multi-AUV: Task allocation, path planning, and formation control

被引：41

作者：

Wang, Linling ^{[1
]}

Zhu, Daqi ^{[2
]}

Pang, Wen ^{[2
]}

Zhang, Youmin ^{[3
]}

机构：

[1] Shanghai Maritime Univ, Shanghai Engn Res Ctr Intelligent Maritime Search, Haigang Ave 1550, Shanghai 201306, Peoples R China

[2] Univ Shanghai Sci & Technol, Sch Mech Engn, Jungong Rd 516, Shanghai 200093, Peoples R China

[3] Concordia Univ, Dept Mech Ind & Aerosp Engn, Montreal, PQ H3G 1M8, Canada

来源：

OCEAN ENGINEERING | 2023年 / 278卷

基金：

中国国家自然科学基金; 加拿大自然科学与工程研究理事会;

关键词：

Autonomous underwater vehicle (AUV); Underwater search; Task allocation; Path planning; Formation control; VARYING FORMATION CONTROL; SELF-ORGANIZING MAP; COMPLETE COVERAGE; VEHICLES SUBJECT; ALGORITHM; ASSIGNMENT; OPTIMIZATION; COORDINATION; ROBOTS; ENVIRONMENTS;

D O I：

10.1016/j.oceaneng.2023.114393

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：

There are significant advantages using the autonomous underwater vehicle (AUV) for underwater search. Compared with a single AUV, multi-AUV offers greater efficiency and better stability in underwater search. At the same time, the theoretical and technical level of autonomous navigation and cooperative control of multi-AUV formation is the key to the implementation of the underwater search task. The following key factors are worth discussing in the application of multi-AUV in underwater search: task allocation, path planning, and formation control. The purpose of this paper is to grasp the application and development trend of multi-AUV formation in underwater search, so as to summarize the past, present, and future research and development trends of this investigation field in detail.

引用

页数：19

共 50 条

[21] Consensus Based Distributive Task Allocation for Multi-AUV in Searching and Detecting
Wu, Di
Zhang, Liukun
Hao, Lichao
2021 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2021), 2021, : 1448 - 1453
[22] Multi-AUV Target Search Based on Bioinspired Neurodynamics Model in 3-D Underwater Environments
Cao, Xiang
Zhu, Daqi
Yang, Simon X.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (11) : 2364 - 2374
[23] Distributed Path-Following Formation Control of Multi-AUV Based on Graph Laplacian
Shi, Linlin
Liu, Meiqin
Zheng, Ronghao
Zhang, Senlin
Zhou, Tian
2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 6983 - 6989
[24] A Survey of Cooperative Hunting Control Algorithms for Multi-AUV Systems
Cao Xiang
Zhu Daqi
2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 5791 - 5795
[25] A Multi-AUV Bearings-Only Multi-target Tracking Method Based on the Fast LMB Filter
Zhang, Yuexing
Li, Yiping
Li, Shuo
Zeng, Junbao
Li, Liang
Xu, Gaopeng
Gao, Peiyan
2022 4TH INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS, ICCR, 2022, : 446 - 451
[26] Formation consensus control of multi-AUV system with switching topology
Zhang X.
Zhou L.
Xing W.
Yao S.
Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University, 2023, 44 (04): : 587 - 593
[27] A Cooperative Evolutionary Computation Algorithm for Dynamic Multiobjective Multi-AUV Path Planning
Liu, Xiao-Fang
Fang, Yongchun
Zhan, Zhi-Hui
Jiang, Yun-Liang
Zhang, Jun
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 20 (01) : 669 - 680
[28] Cooperative path planning for multi-AUV in time-varying ocean flows
Liu, Mingyong
Xu, Baogui
Peng, Xingguang
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2016, 27 (03) : 612 - 618
[29] Based on Improved Bio-Inspired Model for Path Planning by Multi-AUV
Wu, Lian
Li, Yiping
Liu, Jian
PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON ELECTRONICS AND ELECTRICAL ENGINEERING TECHNOLOGY (EEET 2018), 2018, : 128 - 134
[30] Obstacle Avoidance Capability for Multi-Target Path Planning in Different Styles of Search
Alhassow, Mustafa Mohammed
Ata, Oguz
Atilla, Dogu Cagdas
Computers, Materials and Continua, 2024, 81 (01): : 749 - 771

← 1 2 3 4 5 →