{"title":"基于混沌编码的微型移动机器人模糊控制器进化设计","authors":"Rodney A. Gomez, Katherine Lugo, Eric Vallejo","doi":"10.1109/ISEFS.2006.251164","DOIUrl":null,"url":null,"abstract":"The design of fuzzy controllers for mobile robots navigation in different environments has been considered a difficult task for a long time. In this paper, an evolutionary strategy is developed in which a genetic algorithm builds the rules base of a fuzzy controller during training sessions. The potential of the scheme has been shown in the simulated and real Khepera robot","PeriodicalId":269492,"journal":{"name":"2006 International Symposium on Evolving Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evolutionary Design of Fuzzy Controllers Based on Messy Coding for a Miniature Mobile Robot\",\"authors\":\"Rodney A. Gomez, Katherine Lugo, Eric Vallejo\",\"doi\":\"10.1109/ISEFS.2006.251164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The design of fuzzy controllers for mobile robots navigation in different environments has been considered a difficult task for a long time. In this paper, an evolutionary strategy is developed in which a genetic algorithm builds the rules base of a fuzzy controller during training sessions. The potential of the scheme has been shown in the simulated and real Khepera robot\",\"PeriodicalId\":269492,\"journal\":{\"name\":\"2006 International Symposium on Evolving Fuzzy Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Symposium on Evolving Fuzzy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISEFS.2006.251164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Symposium on Evolving Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISEFS.2006.251164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evolutionary Design of Fuzzy Controllers Based on Messy Coding for a Miniature Mobile Robot
The design of fuzzy controllers for mobile robots navigation in different environments has been considered a difficult task for a long time. In this paper, an evolutionary strategy is developed in which a genetic algorithm builds the rules base of a fuzzy controller during training sessions. The potential of the scheme has been shown in the simulated and real Khepera robot
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