The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning
In order to improve the obstacle avoidance and endurance capability of quadrotor UAVs performing tasks such as forest inspection and rescue search, this paper proposes improvements to address the problems of too many traversed nodes, too many redundant corners, too-large turning angles and unsmooth...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/7/4290 |
| _version_ | 1797608357779996672 |
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| author | Jiale Li Feng Kang Chongchong Chen Siyuan Tong Yalan Jia Chenxi Zhang Yaxiong Wang |
| author_facet | Jiale Li Feng Kang Chongchong Chen Siyuan Tong Yalan Jia Chenxi Zhang Yaxiong Wang |
| author_sort | Jiale Li |
| collection | DOAJ |
| description | In order to improve the obstacle avoidance and endurance capability of quadrotor UAVs performing tasks such as forest inspection and rescue search, this paper proposes improvements to address the problems of too many traversed nodes, too many redundant corners, too-large turning angles and unsmooth generated paths in the traditional A* algorithm in path planning. The traditional A* algorithm is improved by using a segmented evaluation function with dynamic heuristic and weighting processing, a steering cost heuristic function based on heading angle deviation control, a redundant turning points removal strategy, and a quasi-uniform cubic b-spline. Through the test comparison of different complexity map scenarios, it is found that the improved A* algorithm reduces the number of traversed nodes by 64.87% on average, the total turning angle by 54.53% on average, the path search time by 49.64% on average, and the path length by 12.52% on average compared to the traditional A* algorithm, and there is no obvious turning point in the path. The real-world applicability of the improved A* algorithm is confirmed by comparing the effect of different algorithms on obstacle avoidance in a map of a real plantation forest environment. |
| first_indexed | 2024-03-11T05:43:19Z |
| format | Article |
| id | doaj.art-e0003ddc5bd34985baa39baed7a679b5 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T05:43:19Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e0003ddc5bd34985baa39baed7a679b52023-11-17T16:18:14ZengMDPI AGApplied Sciences2076-34172023-03-01137429010.3390/app13074290The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path PlanningJiale Li0Feng Kang1Chongchong Chen2Siyuan Tong3Yalan Jia4Chenxi Zhang5Yaxiong Wang6Key Laboratory of State Forestry and Grassland Administration on Forestry Equipment and Automation, School of Technology, Beijing Forestry University, Beijing 100083, ChinaKey Laboratory of State Forestry and Grassland Administration on Forestry Equipment and Automation, School of Technology, Beijing Forestry University, Beijing 100083, ChinaKey Laboratory of State Forestry and Grassland Administration on Forestry Equipment and Automation, School of Technology, Beijing Forestry University, Beijing 100083, ChinaKey Laboratory of State Forestry and Grassland Administration on Forestry Equipment and Automation, School of Technology, Beijing Forestry University, Beijing 100083, ChinaUAV Center Amy Aviation Institute, Beijing 101116, ChinaKey Laboratory of State Forestry and Grassland Administration on Forestry Equipment and Automation, School of Technology, Beijing Forestry University, Beijing 100083, ChinaKey Laboratory of State Forestry and Grassland Administration on Forestry Equipment and Automation, School of Technology, Beijing Forestry University, Beijing 100083, ChinaIn order to improve the obstacle avoidance and endurance capability of quadrotor UAVs performing tasks such as forest inspection and rescue search, this paper proposes improvements to address the problems of too many traversed nodes, too many redundant corners, too-large turning angles and unsmooth generated paths in the traditional A* algorithm in path planning. The traditional A* algorithm is improved by using a segmented evaluation function with dynamic heuristic and weighting processing, a steering cost heuristic function based on heading angle deviation control, a redundant turning points removal strategy, and a quasi-uniform cubic b-spline. Through the test comparison of different complexity map scenarios, it is found that the improved A* algorithm reduces the number of traversed nodes by 64.87% on average, the total turning angle by 54.53% on average, the path search time by 49.64% on average, and the path length by 12.52% on average compared to the traditional A* algorithm, and there is no obvious turning point in the path. The real-world applicability of the improved A* algorithm is confirmed by comparing the effect of different algorithms on obstacle avoidance in a map of a real plantation forest environment.https://www.mdpi.com/2076-3417/13/7/4290UAVimproved A* algorithmpath planningremove redundant turning pointspath smoothing |
| spellingShingle | Jiale Li Feng Kang Chongchong Chen Siyuan Tong Yalan Jia Chenxi Zhang Yaxiong Wang The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning Applied Sciences UAV improved A* algorithm path planning remove redundant turning points path smoothing |
| title | The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning |
| title_full | The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning |
| title_fullStr | The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning |
| title_full_unstemmed | The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning |
| title_short | The Improved A* Algorithm for Quadrotor UAVs under Forest Obstacle Avoidance Path Planning |
| title_sort | improved a algorithm for quadrotor uavs under forest obstacle avoidance path planning |
| topic | UAV improved A* algorithm path planning remove redundant turning points path smoothing |
| url | https://www.mdpi.com/2076-3417/13/7/4290 |
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