Meng-yun S. Liu, Jiyang Dai, Jin Ying, Liang Lu, Guang-jian Tian, Qi Tang
{"title":"Multi-UAV coordinated track planning method based on MSISOS algorithm","authors":"Meng-yun S. Liu, Jiyang Dai, Jin Ying, Liang Lu, Guang-jian Tian, Qi Tang","doi":"10.1117/12.2655678","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of multi-UAV coordinated track planning in complex battlefield environment, this paper proposes a track planning method based on Multi-Strategy Improvement Symbiotic Organisms Search (MSISOS). Firstly, UAV track planning model is established. Then, the adaptive strategy is adopted in mutualism and commensalism phase, to balance the algorithm’s development and exploration, and the introduction of normal disturbance strategy in parasitism phase effectively avoids precocity. Finally, a distributed multi-UAV collaborative trajectory planning method is designed, which uses MSISOS algorithm to solve track planning problem, and harmonizes time and space constraints through the multi-UAV information interaction layer. The simulation results show that MSISOS algorithm compared with MSASOS, PSO and DE algorithms has the best accuracy and convergence speed, and solves complex multi-dimensional multi-UAV coordinated track planning issues.","PeriodicalId":312603,"journal":{"name":"Conference on Intelligent and Human-Computer Interaction Technology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on Intelligent and Human-Computer Interaction Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2655678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to solve the problem of multi-UAV coordinated track planning in complex battlefield environment, this paper proposes a track planning method based on Multi-Strategy Improvement Symbiotic Organisms Search (MSISOS). Firstly, UAV track planning model is established. Then, the adaptive strategy is adopted in mutualism and commensalism phase, to balance the algorithm’s development and exploration, and the introduction of normal disturbance strategy in parasitism phase effectively avoids precocity. Finally, a distributed multi-UAV collaborative trajectory planning method is designed, which uses MSISOS algorithm to solve track planning problem, and harmonizes time and space constraints through the multi-UAV information interaction layer. The simulation results show that MSISOS algorithm compared with MSASOS, PSO and DE algorithms has the best accuracy and convergence speed, and solves complex multi-dimensional multi-UAV coordinated track planning issues.