Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach
To address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO). For improved usability, the entire system adopts a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/5/843 |
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| author | Jianhui Wang Zhiqiang Lu Xunjie Hong Zeye Wu Weihua Li |
| author_facet | Jianhui Wang Zhiqiang Lu Xunjie Hong Zeye Wu Weihua Li |
| author_sort | Jianhui Wang |
| collection | DOAJ |
| description | To address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO). For improved usability, the entire system adopts a fully end-to-end design, with an angular deviation weighting mechanism for stable circular navigation, a novel image-based radar encoding technique for obstacle perception and a decoupled navigation and obstacle avoidance architecture that splits the complex task into three independently trained modules. Experiments validate that both navigation modules exhibit robustness and generalization capabilities, while the obstacle avoidance module partially achieves International Regulations for Preventing Collisions at Sea (COLREGs)-compliant maneuvers. Further tests in continuous multi-buoy inspection tasks confirm the architecture’s effectiveness in integrating these modules to complete the full task. |
| format | Article |
| id | doaj-art-cc87a0a837c34f11a9d14ae6d8a7214d |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-cc87a0a837c34f11a9d14ae6d8a7214d2025-08-20T02:33:50ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-04-0113584310.3390/jmse13050843Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning ApproachJianhui Wang0Zhiqiang Lu1Xunjie Hong2Zeye Wu3Weihua Li4School of Intelligent Science and Engineering, Jinan University, Zhuhai 519000, ChinaSchool of International Energy, Jinan University, Zhuhai 519000, ChinaSchool of International Energy, Jinan University, Zhuhai 519000, ChinaSchool of International Energy, Jinan University, Zhuhai 519000, ChinaSchool of International Energy, Jinan University, Zhuhai 519000, ChinaTo address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO). For improved usability, the entire system adopts a fully end-to-end design, with an angular deviation weighting mechanism for stable circular navigation, a novel image-based radar encoding technique for obstacle perception and a decoupled navigation and obstacle avoidance architecture that splits the complex task into three independently trained modules. Experiments validate that both navigation modules exhibit robustness and generalization capabilities, while the obstacle avoidance module partially achieves International Regulations for Preventing Collisions at Sea (COLREGs)-compliant maneuvers. Further tests in continuous multi-buoy inspection tasks confirm the architecture’s effectiveness in integrating these modules to complete the full task.https://www.mdpi.com/2077-1312/13/5/843buoy inspectioncollision avoidancedeep reinforcement learning (DRL)proximal policy optimization (PPO)unmanned surface vehicle (USV) |
| spellingShingle | Jianhui Wang Zhiqiang Lu Xunjie Hong Zeye Wu Weihua Li Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach Journal of Marine Science and Engineering buoy inspection collision avoidance deep reinforcement learning (DRL) proximal policy optimization (PPO) unmanned surface vehicle (USV) |
| title | Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach |
| title_full | Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach |
| title_fullStr | Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach |
| title_full_unstemmed | Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach |
| title_short | Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach |
| title_sort | navigation and obstacle avoidance for usv in autonomous buoy inspection a deep reinforcement learning approach |
| topic | buoy inspection collision avoidance deep reinforcement learning (DRL) proximal policy optimization (PPO) unmanned surface vehicle (USV) |
| url | https://www.mdpi.com/2077-1312/13/5/843 |
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