Home Journals Articles Updates About
CN
image
收藏切换
Multi-AUV multi-regional coverage path planning based on coevolution
收藏切换
PDF
Chang Cai1, Dan Chen1, Lei Cai2, *
Haiyang Xuebao | 2024, 46(11) : 115 - 124
Less
收藏切换
Haiyang Xuebao | 2024, 46(11): 115-124
• Article •
Multi-AUV multi-regional coverage path planning based on coevolution
Full
Chang Cai1, Dan Chen1, Lei Cai2, *
Affiliations
  • 1. School of Information and Science Technology, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
  • 2. School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
Published: 2024-11-01 doi: 10.12284/hyxb2024132
Outline
收藏切换

In response to contingencies that arise during the underwater coverage missions of multiple autonomous underwater vehicles (AUVs), this study addresses the problem of coverage path replanning for multiple AUVs. A multi-robot multi-regional coverage path planning (M2CPP) method is proposed to reassign uncovered areas to available AUVs and plan their coverage paths. Initially, the lawnmower algorithm is employed to determine the internal paths and candidate entry points within each region. Subsequently, a coevolutionary approach is utilized to solve for the optimal region allocation, region sequence, and the best entry points for each region. Three populations coevolve collaboratively to determine the complete paths for all AUVs, ensuring population diversity and preventing convergence into local optima. Simulation results demonstrate that the proposed method not only replans shorter paths for multiple AUVs based on their initial positions and remaining energy but also optimizes the path structure to ensure a balanced workload among the AUVs, effectively resolving the replanning issue under such scenarios.

multi-robot multi-regional coverage path planning  /  coverage path replanning  /  multi-AUV system  /  coevolution  /  task allocation
Chang Cai, Dan Chen, Lei Cai. Multi-AUV multi-regional coverage path planning based on coevolution[J]. Haiyang Xuebao, 2024 , 46 (11) : 115 -124 . DOI: 10.12284/hyxb2024132
Appendix
Less
Year 2024 volume 46 Issue 11
PDF
188
76
Cite this Article
BibTeX
Article Info
doi: 10.12284/hyxb2024132
  • Receive Date：2024-09-02
  • Online Date：2025-11-26
  • Published：2024-11-01
Article Data
Affiliations
History
  • Received：2024-09-02
  • Revised：2024-11-04
Funding
Affiliations
    1. School of Information and Science Technology, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
    2. School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
References
Share
https://castjournals.cast.org.cn/joweb/hyxb/EN/10.12284/hyxb2024132
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House