Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm
Aiming at the path planning problem of an unmanned aerial vehicle (UAV) in a complex unknown environment, this paper proposes a cooperative path planning algorithm for multiple UAVs. Using the local environment information, several rolling path plannings are carried out by the Artificial Potential F...
| 發表在: | Drones |
|---|---|
| Main Authors: | , , , , |
| 格式: | Article |
| 語言: | 英语 |
| 出版: |
MDPI AG
2025-02-01
|
| 主題: | |
| 在線閱讀: | https://www.mdpi.com/2504-446X/9/3/177 |
| _version_ | 1849746428518203392 |
|---|---|
| author | Cailong Wu Zhengyu Guo Jian Zhang Kai Mao Delin Luo |
| author_facet | Cailong Wu Zhengyu Guo Jian Zhang Kai Mao Delin Luo |
| author_sort | Cailong Wu |
| collection | DOAJ |
| container_title | Drones |
| description | Aiming at the path planning problem of an unmanned aerial vehicle (UAV) in a complex unknown environment, this paper proposes a cooperative path planning algorithm for multiple UAVs. Using the local environment information, several rolling path plannings are carried out by the Artificial Potential Field Bidirectional-Rapidly exploring Random Trees (APF B-RRT*) algorithm. The APF B-RRT* algorithm optimizes the search space by pre-sampling and adapts with an adaptive step while fusing with the APF algorithm for guiding sampling. Then, the generated path is trimmed and smoothed to obtain the optimized path. Then, through the sampling constraint, several paths can be planned at the same time, which are guaranteed not to collide. The model predictive control (MPC) is used to realize the cooperative control of the UAVs, that is, the UAVs reached the destination simultaneously along the planned path. This algorithm achieves some progress in solving the problems of slow convergence speed, an unstable result and an unsmooth path in UAV path planning. Simulation and comparison show that the APF B-RRT* algorithm has certain advantages in algorithm performance. |
| format | Article |
| id | doaj-art-fb06cc599cc54673aaa4e5264e0186f9 |
| institution | Directory of Open Access Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-fb06cc599cc54673aaa4e5264e0186f92025-08-20T01:41:42ZengMDPI AGDrones2504-446X2025-02-019317710.3390/drones9030177Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* AlgorithmCailong Wu0Zhengyu Guo1Jian Zhang2Kai Mao3Delin Luo4School of Aerospace Engineering, Xiamen University, Xiamen 361102, ChinaNational Key Laboratory of Air-Based Information Perception and Fusion, Luoyang 471000, ChinaSchool of Aeronautics, Changji University, Changji 831100, ChinaSchool of Foundation, Naval Aviation University, Yantai 264001, ChinaSchool of Aerospace Engineering, Xiamen University, Xiamen 361102, ChinaAiming at the path planning problem of an unmanned aerial vehicle (UAV) in a complex unknown environment, this paper proposes a cooperative path planning algorithm for multiple UAVs. Using the local environment information, several rolling path plannings are carried out by the Artificial Potential Field Bidirectional-Rapidly exploring Random Trees (APF B-RRT*) algorithm. The APF B-RRT* algorithm optimizes the search space by pre-sampling and adapts with an adaptive step while fusing with the APF algorithm for guiding sampling. Then, the generated path is trimmed and smoothed to obtain the optimized path. Then, through the sampling constraint, several paths can be planned at the same time, which are guaranteed not to collide. The model predictive control (MPC) is used to realize the cooperative control of the UAVs, that is, the UAVs reached the destination simultaneously along the planned path. This algorithm achieves some progress in solving the problems of slow convergence speed, an unstable result and an unsmooth path in UAV path planning. Simulation and comparison show that the APF B-RRT* algorithm has certain advantages in algorithm performance.https://www.mdpi.com/2504-446X/9/3/177cooperative path planningRRT algorithmAPFmultiple UAVsMPC |
| spellingShingle | Cailong Wu Zhengyu Guo Jian Zhang Kai Mao Delin Luo Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm cooperative path planning RRT algorithm APF multiple UAVs MPC |
| title | Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm |
| title_full | Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm |
| title_fullStr | Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm |
| title_full_unstemmed | Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm |
| title_short | Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm |
| title_sort | cooperative path planning for multiple uavs based on apf b rrt algorithm |
| topic | cooperative path planning RRT algorithm APF multiple UAVs MPC |
| url | https://www.mdpi.com/2504-446X/9/3/177 |
| work_keys_str_mv | AT cailongwu cooperativepathplanningformultipleuavsbasedonapfbrrtalgorithm AT zhengyuguo cooperativepathplanningformultipleuavsbasedonapfbrrtalgorithm AT jianzhang cooperativepathplanningformultipleuavsbasedonapfbrrtalgorithm AT kaimao cooperativepathplanningformultipleuavsbasedonapfbrrtalgorithm AT delinluo cooperativepathplanningformultipleuavsbasedonapfbrrtalgorithm |