{"title":"基于KF-RRT算法的无人机动态路径规划","authors":"Hang Yan, Xingjian Fu","doi":"10.1109/DDCLS58216.2023.10166695","DOIUrl":null,"url":null,"abstract":"For the dynamic path planning of UAV, an algorithm based on Kalman Filter and improved Rapid-exploration Random Tree (KF-RRT) is proposed. Firstly, on the basis of the RRT algorithm, the weight coefficient of the target area trend is added, which reduces the time of UAV path planning. Secondly, the prediction function of Kalman Filter is added to predict the motion trajectory of dynamic obstacles in advance. Then, B-spline curve is used for smoothing to plan the feasible path of UAV. Finally, the KF-RRT algorithm in this paper is compared with other RRT algorithms by simulation, which shows that the proposed algorithm is more suitable for the dynamic path planning of UAV.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic Path Planning of UAV Based on KF-RRT Algorithm\",\"authors\":\"Hang Yan, Xingjian Fu\",\"doi\":\"10.1109/DDCLS58216.2023.10166695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the dynamic path planning of UAV, an algorithm based on Kalman Filter and improved Rapid-exploration Random Tree (KF-RRT) is proposed. Firstly, on the basis of the RRT algorithm, the weight coefficient of the target area trend is added, which reduces the time of UAV path planning. Secondly, the prediction function of Kalman Filter is added to predict the motion trajectory of dynamic obstacles in advance. Then, B-spline curve is used for smoothing to plan the feasible path of UAV. Finally, the KF-RRT algorithm in this paper is compared with other RRT algorithms by simulation, which shows that the proposed algorithm is more suitable for the dynamic path planning of UAV.\",\"PeriodicalId\":415532,\"journal\":{\"name\":\"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DDCLS58216.2023.10166695\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS58216.2023.10166695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Path Planning of UAV Based on KF-RRT Algorithm
For the dynamic path planning of UAV, an algorithm based on Kalman Filter and improved Rapid-exploration Random Tree (KF-RRT) is proposed. Firstly, on the basis of the RRT algorithm, the weight coefficient of the target area trend is added, which reduces the time of UAV path planning. Secondly, the prediction function of Kalman Filter is added to predict the motion trajectory of dynamic obstacles in advance. Then, B-spline curve is used for smoothing to plan the feasible path of UAV. Finally, the KF-RRT algorithm in this paper is compared with other RRT algorithms by simulation, which shows that the proposed algorithm is more suitable for the dynamic path planning of UAV.