Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method
The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm that combines task allocation and path planning t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/1/179 |
| _version_ | 1797343280378150912 |
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| author | Jing Luo Yuhang Zhang Jiayuan Zhuang Yumin Su |
| author_facet | Jing Luo Yuhang Zhang Jiayuan Zhuang Yumin Su |
| author_sort | Jing Luo |
| collection | DOAJ |
| description | The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm that combines task allocation and path planning to improve mission efficiency. The algorithm introduces a novel approach based on a self-attention mechanism (SAM) for intelligent task allocation. The key contribution lies in the integration of an adaptive distance field, created using the locking sweeping method (LSM), into the SAM. This integration enables the algorithm to determine the minimum practical sailing distance in obstacle-filled environments. The algorithm efficiently generates task execution sequences in cluttered maritime environments with numerous obstacles. By incorporating a safety parameter, the enhanced SAM algorithm adapts the dimensional influence of obstacles and generates paths that ensure the safety of the USV. The algorithms have been thoroughly evaluated and validated through extensive computer-based simulations, demonstrating their effectiveness in both simulated and practical maritime environments. The results of the simulations verify the algorithm’s capability to optimize task allocation and path planning, leading to improved performance in complex and obstacle-laden scenarios. |
| first_indexed | 2024-03-08T10:45:25Z |
| format | Article |
| id | doaj.art-8e2f0df2194a4c0c8a1426aae6d43a3e |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-08T10:45:25Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-8e2f0df2194a4c0c8a1426aae6d43a3e2024-01-26T17:17:45ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-01-0112117910.3390/jmse12010179Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping MethodJing Luo0Yuhang Zhang1Jiayuan Zhuang2Yumin Su3Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, ChinaJiangsu Automation Research Institute, Lianyungang 222061, ChinaScience and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, ChinaScience and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, ChinaThe development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm that combines task allocation and path planning to improve mission efficiency. The algorithm introduces a novel approach based on a self-attention mechanism (SAM) for intelligent task allocation. The key contribution lies in the integration of an adaptive distance field, created using the locking sweeping method (LSM), into the SAM. This integration enables the algorithm to determine the minimum practical sailing distance in obstacle-filled environments. The algorithm efficiently generates task execution sequences in cluttered maritime environments with numerous obstacles. By incorporating a safety parameter, the enhanced SAM algorithm adapts the dimensional influence of obstacles and generates paths that ensure the safety of the USV. The algorithms have been thoroughly evaluated and validated through extensive computer-based simulations, demonstrating their effectiveness in both simulated and practical maritime environments. The results of the simulations verify the algorithm’s capability to optimize task allocation and path planning, leading to improved performance in complex and obstacle-laden scenarios.https://www.mdpi.com/2077-1312/12/1/179USVtask allocationpath planningself-attention mechanismlocking sweeping method |
| spellingShingle | Jing Luo Yuhang Zhang Jiayuan Zhuang Yumin Su Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method Journal of Marine Science and Engineering USV task allocation path planning self-attention mechanism locking sweeping method |
| title | Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method |
| title_full | Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method |
| title_fullStr | Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method |
| title_full_unstemmed | Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method |
| title_short | Intelligent Task Allocation and Planning for Unmanned Surface Vehicle (USV) Using Self-Attention Mechanism and Locking Sweeping Method |
| title_sort | intelligent task allocation and planning for unmanned surface vehicle usv using self attention mechanism and locking sweeping method |
| topic | USV task allocation path planning self-attention mechanism locking sweeping method |
| url | https://www.mdpi.com/2077-1312/12/1/179 |
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