Qiang Fu, Xinghui Lan, Yuanfa Ji, Xiyan Sun, Fenghua Ren
{"title":"启发式RRT融合A*用于无人机三维路径规划","authors":"Qiang Fu, Xinghui Lan, Yuanfa Ji, Xiyan Sun, Fenghua Ren","doi":"10.1109/ITOEC53115.2022.9734628","DOIUrl":null,"url":null,"abstract":"Path planning is the key to the autonomous flight of unmanned aerial vehicle (UAV). Aiming at the problems of blind search, long and zigzag path in the path planning of three-dimensional space environment, A heuristic bidirectional target RRT fusion A* algorithm was proposed. Firstly, the algorithm combines heuristic probability and bias expansion strategy to improve the target orientation of sampling. After obtaining the complete path point, the shortest path is obtained by fusing redundant nodes in the complete path of A* algorithm. Finally, B-spline algorithm is used to smooth the path, which obtains a smooth feasible path. Experimental results show that compared with the traditional B-RRT algorithm, the improved B-RRT algorithm improves the node utilization by 9.6 times, reduces the extension nodes by 86.9%, shorts the search time by 21.46%, and shorts the path by 7.9%.","PeriodicalId":127300,"journal":{"name":"2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Heuristic RRT fusion A* for 3D path planning of UAV\",\"authors\":\"Qiang Fu, Xinghui Lan, Yuanfa Ji, Xiyan Sun, Fenghua Ren\",\"doi\":\"10.1109/ITOEC53115.2022.9734628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Path planning is the key to the autonomous flight of unmanned aerial vehicle (UAV). Aiming at the problems of blind search, long and zigzag path in the path planning of three-dimensional space environment, A heuristic bidirectional target RRT fusion A* algorithm was proposed. Firstly, the algorithm combines heuristic probability and bias expansion strategy to improve the target orientation of sampling. After obtaining the complete path point, the shortest path is obtained by fusing redundant nodes in the complete path of A* algorithm. Finally, B-spline algorithm is used to smooth the path, which obtains a smooth feasible path. Experimental results show that compared with the traditional B-RRT algorithm, the improved B-RRT algorithm improves the node utilization by 9.6 times, reduces the extension nodes by 86.9%, shorts the search time by 21.46%, and shorts the path by 7.9%.\",\"PeriodicalId\":127300,\"journal\":{\"name\":\"2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITOEC53115.2022.9734628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITOEC53115.2022.9734628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Heuristic RRT fusion A* for 3D path planning of UAV
Path planning is the key to the autonomous flight of unmanned aerial vehicle (UAV). Aiming at the problems of blind search, long and zigzag path in the path planning of three-dimensional space environment, A heuristic bidirectional target RRT fusion A* algorithm was proposed. Firstly, the algorithm combines heuristic probability and bias expansion strategy to improve the target orientation of sampling. After obtaining the complete path point, the shortest path is obtained by fusing redundant nodes in the complete path of A* algorithm. Finally, B-spline algorithm is used to smooth the path, which obtains a smooth feasible path. Experimental results show that compared with the traditional B-RRT algorithm, the improved B-RRT algorithm improves the node utilization by 9.6 times, reduces the extension nodes by 86.9%, shorts the search time by 21.46%, and shorts the path by 7.9%.