{"title":"复杂环境下固定翼飞行器的实时避障","authors":"Rong Ma, Wenrui Ma, Xiaolong Chen, Jia Li","doi":"10.1109/CGNCC.2016.7828835","DOIUrl":null,"url":null,"abstract":"In this paper, we present a real-time obstacle avoidance method for fixed-wing unmanned aerial vehicles (UAVs) in complex environment. The Rapidly-exploring Random Tree(RRT) algorithm is used in this method. In order to adapt the RRT algorithm on fixed-wing platforms, we make extensions on it. The algorithm demonstrates very good performance in trajectory planning for fixed-wing vehicles in three-dimensional environment and dynamic environment. We analyze the algorithm theoretically and provide simulation results. We also demonstrate our method on a fixed-wing vehicle flying over a runway with multiple obstacles. The application of this method will greatly improve the survival ability of fixed-wing vehicles in complex environment. It is significant in elevation of autonomous level of UAV.","PeriodicalId":426650,"journal":{"name":"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Real-time obstacle avoidance for fixed-wing vehicles in complex environment\",\"authors\":\"Rong Ma, Wenrui Ma, Xiaolong Chen, Jia Li\",\"doi\":\"10.1109/CGNCC.2016.7828835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a real-time obstacle avoidance method for fixed-wing unmanned aerial vehicles (UAVs) in complex environment. The Rapidly-exploring Random Tree(RRT) algorithm is used in this method. In order to adapt the RRT algorithm on fixed-wing platforms, we make extensions on it. The algorithm demonstrates very good performance in trajectory planning for fixed-wing vehicles in three-dimensional environment and dynamic environment. We analyze the algorithm theoretically and provide simulation results. We also demonstrate our method on a fixed-wing vehicle flying over a runway with multiple obstacles. The application of this method will greatly improve the survival ability of fixed-wing vehicles in complex environment. It is significant in elevation of autonomous level of UAV.\",\"PeriodicalId\":426650,\"journal\":{\"name\":\"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CGNCC.2016.7828835\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGNCC.2016.7828835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time obstacle avoidance for fixed-wing vehicles in complex environment
In this paper, we present a real-time obstacle avoidance method for fixed-wing unmanned aerial vehicles (UAVs) in complex environment. The Rapidly-exploring Random Tree(RRT) algorithm is used in this method. In order to adapt the RRT algorithm on fixed-wing platforms, we make extensions on it. The algorithm demonstrates very good performance in trajectory planning for fixed-wing vehicles in three-dimensional environment and dynamic environment. We analyze the algorithm theoretically and provide simulation results. We also demonstrate our method on a fixed-wing vehicle flying over a runway with multiple obstacles. The application of this method will greatly improve the survival ability of fixed-wing vehicles in complex environment. It is significant in elevation of autonomous level of UAV.