{"title":"基于关键航迹点的多无人机协同航迹规划","authors":"Xu Yang, Huang Gang","doi":"10.1145/3483845.3483854","DOIUrl":null,"url":null,"abstract":"Multi-UAVs cooperative trajectory planning (MUCTP) refers to planning a number of safe, reliable and non-collision from each UAV starting point to the target point in known, partially known or unknown environment. In the planning process, it is necessary to consider the constraints of the UAV itself and the synergistic restriction relationship. Therefore, in order to improve the efficiency of collaborative path planning, a multi-UAVs collaborative path planning algorithm based on key path points is proposed in this paper. In this algorithm, the gene location representation method of individual population was defined, the feasible domain of three-dimensional space was set, and the objective function was constructed by combining the constraint conditions. The experimental results show that the algorithm proposed in this paper has fast convergence speed and strong synergistic ability in multi-UAVs cooperative path planning, which makes the planned track group more reasonable.","PeriodicalId":134636,"journal":{"name":"Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Coordinated path planning for Multi-UAVs based on critical track points\",\"authors\":\"Xu Yang, Huang Gang\",\"doi\":\"10.1145/3483845.3483854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-UAVs cooperative trajectory planning (MUCTP) refers to planning a number of safe, reliable and non-collision from each UAV starting point to the target point in known, partially known or unknown environment. In the planning process, it is necessary to consider the constraints of the UAV itself and the synergistic restriction relationship. Therefore, in order to improve the efficiency of collaborative path planning, a multi-UAVs collaborative path planning algorithm based on key path points is proposed in this paper. In this algorithm, the gene location representation method of individual population was defined, the feasible domain of three-dimensional space was set, and the objective function was constructed by combining the constraint conditions. The experimental results show that the algorithm proposed in this paper has fast convergence speed and strong synergistic ability in multi-UAVs cooperative path planning, which makes the planned track group more reasonable.\",\"PeriodicalId\":134636,\"journal\":{\"name\":\"Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3483845.3483854\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3483845.3483854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coordinated path planning for Multi-UAVs based on critical track points
Multi-UAVs cooperative trajectory planning (MUCTP) refers to planning a number of safe, reliable and non-collision from each UAV starting point to the target point in known, partially known or unknown environment. In the planning process, it is necessary to consider the constraints of the UAV itself and the synergistic restriction relationship. Therefore, in order to improve the efficiency of collaborative path planning, a multi-UAVs collaborative path planning algorithm based on key path points is proposed in this paper. In this algorithm, the gene location representation method of individual population was defined, the feasible domain of three-dimensional space was set, and the objective function was constructed by combining the constraint conditions. The experimental results show that the algorithm proposed in this paper has fast convergence speed and strong synergistic ability in multi-UAVs cooperative path planning, which makes the planned track group more reasonable.