{"title":"基于分布式避障控制的无人机群编队维护与重构方法","authors":"Xiaowei Fu, Jing Pan, Haixiang Wang, Xiao-guang Gao","doi":"10.1109/ANZCC47194.2019.8945601","DOIUrl":null,"url":null,"abstract":"This paper studies the problem of formation maintenance and reconstruction of UAV swarm with obstacle avoidance. Firstly, a collision prediction mechanism is introduced to determine whether each UAV needs to avoid obstacles or not. Secondly, by designing the position and speed consistency control law between UAVs, each UAV and the virtual leader, combined with the obstacle avoidance mechanism based on the artificial potential field method, the swarm formation control and maintenance algorithm with obstacle avoidance is realized. Finally, the formation transformation is realized by changing the relative positional relationship between each UAV and the virtual leader. The simulation results show that the UAV swarm can generate, maintain and reconstruct the expected formation in a real-time distributed manner while avoiding obstacles.","PeriodicalId":322243,"journal":{"name":"2019 Australian & New Zealand Control Conference (ANZCC)","volume":"469 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Formation Maintenance and Reconstruction Method of UAV Swarm based on Distributed Control with Obstacle Avoidance\",\"authors\":\"Xiaowei Fu, Jing Pan, Haixiang Wang, Xiao-guang Gao\",\"doi\":\"10.1109/ANZCC47194.2019.8945601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the problem of formation maintenance and reconstruction of UAV swarm with obstacle avoidance. Firstly, a collision prediction mechanism is introduced to determine whether each UAV needs to avoid obstacles or not. Secondly, by designing the position and speed consistency control law between UAVs, each UAV and the virtual leader, combined with the obstacle avoidance mechanism based on the artificial potential field method, the swarm formation control and maintenance algorithm with obstacle avoidance is realized. Finally, the formation transformation is realized by changing the relative positional relationship between each UAV and the virtual leader. The simulation results show that the UAV swarm can generate, maintain and reconstruct the expected formation in a real-time distributed manner while avoiding obstacles.\",\"PeriodicalId\":322243,\"journal\":{\"name\":\"2019 Australian & New Zealand Control Conference (ANZCC)\",\"volume\":\"469 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Australian & New Zealand Control Conference (ANZCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANZCC47194.2019.8945601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Australian & New Zealand Control Conference (ANZCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANZCC47194.2019.8945601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Formation Maintenance and Reconstruction Method of UAV Swarm based on Distributed Control with Obstacle Avoidance
This paper studies the problem of formation maintenance and reconstruction of UAV swarm with obstacle avoidance. Firstly, a collision prediction mechanism is introduced to determine whether each UAV needs to avoid obstacles or not. Secondly, by designing the position and speed consistency control law between UAVs, each UAV and the virtual leader, combined with the obstacle avoidance mechanism based on the artificial potential field method, the swarm formation control and maintenance algorithm with obstacle avoidance is realized. Finally, the formation transformation is realized by changing the relative positional relationship between each UAV and the virtual leader. The simulation results show that the UAV swarm can generate, maintain and reconstruct the expected formation in a real-time distributed manner while avoiding obstacles.