A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems
Investigating the applications and challenges of multi-robot pursuit-evasion problems in underwater environments holds significant importance for enhancing the autonomous decision-making and collaborative capabilities of underwater robot systems. By searching the Web of Science Core Collection datab...
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Science Press (China)
2025-06-01
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| Series: | 水下无人系统学报 |
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| Online Access: | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2025-0032 |
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| author | Zhenkun LEI Mingzhi CHEN Daqi ZHU |
| author_facet | Zhenkun LEI Mingzhi CHEN Daqi ZHU |
| author_sort | Zhenkun LEI |
| collection | DOAJ |
| description | Investigating the applications and challenges of multi-robot pursuit-evasion problems in underwater environments holds significant importance for enhancing the autonomous decision-making and collaborative capabilities of underwater robot systems. By searching the Web of Science Core Collection database, over 2 200 relevant literatures published between 2004 and 2024 were screened, and a comprehensive analysis was conducted on the definition of pursuit-evasion problems, research status, intelligent pursuit-evasion methods, and their applications in underwater environments. The principles, advantages, disadvantages, and applicability of four intelligent pursuit-evasion methods, including reinforcement learning, model predictive control, Apollonius circle, and artificial potential field, were analyzed in depth. The study reveals that reinforcement learning optimizes strategies through training to adapt to complex environments but suffers from a long training cycle; model predictive control formulates strategies based on future state predictions, boasting high accuracy but facing real-time challenges; the Apollonius circle optimizes paths using geometric relationships; and the artificial potential field method guides robots with virtual force fields. In underwater environments, robot pursuit-evasion games confront multiple challenges, such as ocean current disturbances and limited communication. This paper summarizes the application potential and existing issues of current methods in underwater environments and proposes future research directions, including the development of more efficient and adaptive intelligent pursuit-evasion algorithms, so as to address the technical requirements of complex underwater environments and provide theoretical references for designing pursuit-evasion strategies for underwater multi-robot systems. |
| format | Article |
| id | doaj-art-3bd7dbb052424eb7a51ef2f37aeb0821 |
| institution | Kabale University |
| issn | 2096-3920 |
| language | zho |
| publishDate | 2025-06-01 |
| publisher | Science Press (China) |
| record_format | Article |
| series | 水下无人系统学报 |
| spelling | doaj-art-3bd7dbb052424eb7a51ef2f37aeb08212025-08-20T03:33:07ZzhoScience Press (China)水下无人系统学报2096-39202025-06-0133348449410.11993/j.issn.2096-3920.2025-00322025-0032A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion ProblemsZhenkun LEI0Mingzhi CHEN1Daqi ZHU2School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, ChinaSchool of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, ChinaSchool of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, ChinaInvestigating the applications and challenges of multi-robot pursuit-evasion problems in underwater environments holds significant importance for enhancing the autonomous decision-making and collaborative capabilities of underwater robot systems. By searching the Web of Science Core Collection database, over 2 200 relevant literatures published between 2004 and 2024 were screened, and a comprehensive analysis was conducted on the definition of pursuit-evasion problems, research status, intelligent pursuit-evasion methods, and their applications in underwater environments. The principles, advantages, disadvantages, and applicability of four intelligent pursuit-evasion methods, including reinforcement learning, model predictive control, Apollonius circle, and artificial potential field, were analyzed in depth. The study reveals that reinforcement learning optimizes strategies through training to adapt to complex environments but suffers from a long training cycle; model predictive control formulates strategies based on future state predictions, boasting high accuracy but facing real-time challenges; the Apollonius circle optimizes paths using geometric relationships; and the artificial potential field method guides robots with virtual force fields. In underwater environments, robot pursuit-evasion games confront multiple challenges, such as ocean current disturbances and limited communication. This paper summarizes the application potential and existing issues of current methods in underwater environments and proposes future research directions, including the development of more efficient and adaptive intelligent pursuit-evasion algorithms, so as to address the technical requirements of complex underwater environments and provide theoretical references for designing pursuit-evasion strategies for underwater multi-robot systems.https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2025-0032multi-robot systemspursuit-evasionreinforcement learningmodel predictive controlunderwater robot |
| spellingShingle | Zhenkun LEI Mingzhi CHEN Daqi ZHU A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems 水下无人系统学报 multi-robot systems pursuit-evasion reinforcement learning model predictive control underwater robot |
| title | A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems |
| title_full | A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems |
| title_fullStr | A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems |
| title_full_unstemmed | A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems |
| title_short | A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems |
| title_sort | literature analysis based study on advances in underwater multi robot pursuit evasion problems |
| topic | multi-robot systems pursuit-evasion reinforcement learning model predictive control underwater robot |
| url | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2025-0032 |
| work_keys_str_mv | AT zhenkunlei aliteratureanalysisbasedstudyonadvancesinunderwatermultirobotpursuitevasionproblems AT mingzhichen aliteratureanalysisbasedstudyonadvancesinunderwatermultirobotpursuitevasionproblems AT daqizhu aliteratureanalysisbasedstudyonadvancesinunderwatermultirobotpursuitevasionproblems AT zhenkunlei literatureanalysisbasedstudyonadvancesinunderwatermultirobotpursuitevasionproblems AT mingzhichen literatureanalysisbasedstudyonadvancesinunderwatermultirobotpursuitevasionproblems AT daqizhu literatureanalysisbasedstudyonadvancesinunderwatermultirobotpursuitevasionproblems |