{"title":"Optimal design of infrared motion sensing system using divide-and-conquer based genetic algorithm","authors":"Guodong Feng, Yuebin Yang, Xuemei Guo, Guoli Wang","doi":"10.1109/ICMA.2013.6617965","DOIUrl":null,"url":null,"abstract":"This paper studies the optimal design of an infrared motion sensing system for human motion localization in the context of human-following robots. Specifically, we aim to find the optimal number and placement of bearing-sensitive pyroelectric infrared (PIR) sensor arrays for improving localization performance. This optimal design leads to a multiobjective, mixed-integer-discrete-continuous and variable-dimensional optimization problem, which prevents from using conventional multiobjective optimization techniques including genetic algorithm (GA). This paper explores the use of divide-and-conquer based GA in solving this optimal design problem. The proposed approach consists of three steps: firstly, following divide-and-conquer principle, the optimal design problem is decomposed into a set of sub-optimization problems; then the sub-optimization problems are solved with standard GA; finally, the optimal solution is found through fusing the resulting solutions of sub-optimization problems. The proposed design approach is illustrated with a design example, and verified with experimental studies.","PeriodicalId":335884,"journal":{"name":"2013 IEEE International Conference on Mechatronics and Automation","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2013.6617965","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 studies the optimal design of an infrared motion sensing system for human motion localization in the context of human-following robots. Specifically, we aim to find the optimal number and placement of bearing-sensitive pyroelectric infrared (PIR) sensor arrays for improving localization performance. This optimal design leads to a multiobjective, mixed-integer-discrete-continuous and variable-dimensional optimization problem, which prevents from using conventional multiobjective optimization techniques including genetic algorithm (GA). This paper explores the use of divide-and-conquer based GA in solving this optimal design problem. The proposed approach consists of three steps: firstly, following divide-and-conquer principle, the optimal design problem is decomposed into a set of sub-optimization problems; then the sub-optimization problems are solved with standard GA; finally, the optimal solution is found through fusing the resulting solutions of sub-optimization problems. The proposed design approach is illustrated with a design example, and verified with experimental studies.