3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone
As various fields and industries have progressed, the use of drones has grown tremendously. The problem of path planning for drones flying at low altitude in urban as well as mountainous areas will be crucial for drones performing search-and-rescue missions. In this paper, we propose a convergent ap...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/14/7333 |
| _version_ | 1797407520864600064 |
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| author | Yuan Luo Jiakai Lu Yi Zhang Qiong Qin Yanyu Liu |
| author_facet | Yuan Luo Jiakai Lu Yi Zhang Qiong Qin Yanyu Liu |
| author_sort | Yuan Luo |
| collection | DOAJ |
| description | As various fields and industries have progressed, the use of drones has grown tremendously. The problem of path planning for drones flying at low altitude in urban as well as mountainous areas will be crucial for drones performing search-and-rescue missions. In this paper, we propose a convergent approach to ensure autonomous collision-free path planning for drones in the presence of both static obstacles and dynamic threats. Firstly, this paper extends the jump point search algorithm (JPS) in three dimensions for the drone to generate collision-free paths based on static environments. Next, a parent node transfer law is proposed and used to implement the JPS algorithm for any-angle path planning, which further shortens the planning path of the drones. Furthermore, the optimized paths are smoothed by seventh-order polynomial interpolation based on minimum snap to ensure the continuity at the path nodes. Finally, this paper improves the artificial potential field (APF) method by a virtual gravitational field and 3D Bresenham’s line algorithm to achieve the autonomous obstacle avoidance of drones in a dynamic-threat conflict environment. In this paper, the performance of this convergent approach is verified by simulation experiments. The simulation results show that the proposed approach can effectively solve the path planning and autonomous-obstacle-avoidance problems of drones in low-altitude flight missions. |
| first_indexed | 2024-03-09T03:42:40Z |
| format | Article |
| id | doaj.art-a72e0ef9181a471a8590ac01c651435c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T03:42:40Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-a72e0ef9181a471a8590ac01c651435c2023-12-03T14:38:02ZengMDPI AGApplied Sciences2076-34172022-07-011214733310.3390/app121473333D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search DroneYuan Luo0Jiakai Lu1Yi Zhang2Qiong Qin3Yanyu Liu4Key Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaKey Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaKey Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaAs various fields and industries have progressed, the use of drones has grown tremendously. The problem of path planning for drones flying at low altitude in urban as well as mountainous areas will be crucial for drones performing search-and-rescue missions. In this paper, we propose a convergent approach to ensure autonomous collision-free path planning for drones in the presence of both static obstacles and dynamic threats. Firstly, this paper extends the jump point search algorithm (JPS) in three dimensions for the drone to generate collision-free paths based on static environments. Next, a parent node transfer law is proposed and used to implement the JPS algorithm for any-angle path planning, which further shortens the planning path of the drones. Furthermore, the optimized paths are smoothed by seventh-order polynomial interpolation based on minimum snap to ensure the continuity at the path nodes. Finally, this paper improves the artificial potential field (APF) method by a virtual gravitational field and 3D Bresenham’s line algorithm to achieve the autonomous obstacle avoidance of drones in a dynamic-threat conflict environment. In this paper, the performance of this convergent approach is verified by simulation experiments. The simulation results show that the proposed approach can effectively solve the path planning and autonomous-obstacle-avoidance problems of drones in low-altitude flight missions.https://www.mdpi.com/2076-3417/12/14/7333static obstaclesdynamic threatspath planningtrack optimizationjump point search algorithmartificial potential field |
| spellingShingle | Yuan Luo Jiakai Lu Yi Zhang Qiong Qin Yanyu Liu 3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone Applied Sciences static obstacles dynamic threats path planning track optimization jump point search algorithm artificial potential field |
| title | 3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone |
| title_full | 3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone |
| title_fullStr | 3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone |
| title_full_unstemmed | 3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone |
| title_short | 3D JPS Path Optimization Algorithm and Dynamic-Obstacle Avoidance Design Based on Near-Ground Search Drone |
| title_sort | 3d jps path optimization algorithm and dynamic obstacle avoidance design based on near ground search drone |
| topic | static obstacles dynamic threats path planning track optimization jump point search algorithm artificial potential field |
| url | https://www.mdpi.com/2076-3417/12/14/7333 |
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