A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles
A single unmanned surface combatant (USV) has poor mission execution capability, so the cooperation of multiple unmanned surface ships is widely used. Cooperative hunting is an important aspect of multi USV collaborative research. Therefore, this paper proposed a cooperative hunting method for multi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/16/7058 |
| _version_ | 1797583285007679488 |
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| author | Zhihao Chen Zhiyao Zhao Jiping Xu Xiaoyi Wang Yang Lu Jiabin Yu |
| author_facet | Zhihao Chen Zhiyao Zhao Jiping Xu Xiaoyi Wang Yang Lu Jiabin Yu |
| author_sort | Zhihao Chen |
| collection | DOAJ |
| description | A single unmanned surface combatant (USV) has poor mission execution capability, so the cooperation of multiple unmanned surface ships is widely used. Cooperative hunting is an important aspect of multi USV collaborative research. Therefore, this paper proposed a cooperative hunting method for multi-USV based on the A* algorithm in an environment with obstacles. First, based on the traditional A* algorithm, a path smoothing method based on USV minimum turning radius is proposed. At the same time, the post order traversal recursive algorithm in the binary tree method is used to replace the enumeration algorithm to obtain the optimal path, which improves the efficiency of the A* algorithm. Second, a biomimetic multi USV swarm collaborative hunting method is proposed. Multiple USV clusters simulate the hunting strategy of lions to pre-form on the target’s path, so multiple USV clusters do not require manual formation. During the hunting process, the formation of multiple USV groups is adjusted to limit the movement and turning of the target, thereby reducing the range of activity of the target and improving the effectiveness of the algorithm. To verify the effectiveness of the algorithm, two sets of simulation experiments were conducted. The results show that the algorithm has good performance in path planning and target search. |
| first_indexed | 2024-03-10T23:36:44Z |
| format | Article |
| id | doaj.art-830ee4f8e40c4745becbb8bbcc56ce2c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T23:36:44Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-830ee4f8e40c4745becbb8bbcc56ce2c2023-11-19T02:56:11ZengMDPI AGSensors1424-82202023-08-012316705810.3390/s23167058A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with ObstaclesZhihao Chen0Zhiyao Zhao1Jiping Xu2Xiaoyi Wang3Yang Lu4Jiabin Yu5School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaA single unmanned surface combatant (USV) has poor mission execution capability, so the cooperation of multiple unmanned surface ships is widely used. Cooperative hunting is an important aspect of multi USV collaborative research. Therefore, this paper proposed a cooperative hunting method for multi-USV based on the A* algorithm in an environment with obstacles. First, based on the traditional A* algorithm, a path smoothing method based on USV minimum turning radius is proposed. At the same time, the post order traversal recursive algorithm in the binary tree method is used to replace the enumeration algorithm to obtain the optimal path, which improves the efficiency of the A* algorithm. Second, a biomimetic multi USV swarm collaborative hunting method is proposed. Multiple USV clusters simulate the hunting strategy of lions to pre-form on the target’s path, so multiple USV clusters do not require manual formation. During the hunting process, the formation of multiple USV groups is adjusted to limit the movement and turning of the target, thereby reducing the range of activity of the target and improving the effectiveness of the algorithm. To verify the effectiveness of the algorithm, two sets of simulation experiments were conducted. The results show that the algorithm has good performance in path planning and target search.https://www.mdpi.com/1424-8220/23/16/7058multi-USV swarmpath planningA* algorithmtarget huntingobstacle avoidance |
| spellingShingle | Zhihao Chen Zhiyao Zhao Jiping Xu Xiaoyi Wang Yang Lu Jiabin Yu A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles Sensors multi-USV swarm path planning A* algorithm target hunting obstacle avoidance |
| title | A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles |
| title_full | A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles |
| title_fullStr | A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles |
| title_full_unstemmed | A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles |
| title_short | A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles |
| title_sort | cooperative hunting method for multi usv based on the a algorithm in an environment with obstacles |
| topic | multi-USV swarm path planning A* algorithm target hunting obstacle avoidance |
| url | https://www.mdpi.com/1424-8220/23/16/7058 |
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