{"title":"MPC and SADE for UAV real-time path planning in 3D environment","authors":"Qiang Wang, An Zhang, H. Sun","doi":"10.1109/SPAC.2014.6982672","DOIUrl":null,"url":null,"abstract":"This paper proposed a method of real-time path planning for UAV based on model predictive control and self adaptive differential evolutionary algorithm First the model of three-dimensional path planning of UAV was built by model predictive control Then the encoding method based on deflection angle was given. The constraints were combined with the self adaptive differential evolutionary algorithm to make the path more rational and the searching more efficiently. The simulation analyses showed that the method of path planning is available and efficient, that could satisfy the requirements of terrain following and threat avoidance.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC.2014.6982672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper proposed a method of real-time path planning for UAV based on model predictive control and self adaptive differential evolutionary algorithm First the model of three-dimensional path planning of UAV was built by model predictive control Then the encoding method based on deflection angle was given. The constraints were combined with the self adaptive differential evolutionary algorithm to make the path more rational and the searching more efficiently. The simulation analyses showed that the method of path planning is available and efficient, that could satisfy the requirements of terrain following and threat avoidance.
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