{"title":"自主机器人层次模糊行为学习研究","authors":"Ziying Zhang, Rubo Zhang, Xin Liu","doi":"10.1109/ICICSE.2008.60","DOIUrl":null,"url":null,"abstract":"Aiming at the changing and dynamic unstructured environments of autonomous robot, this paper analyses these kinds of effects on robot in details and thus presents a local plan architecture based on hierarchical fuzzy logic to implement the basic navigation behaviors and the coordination between these behaviors to produce a type-2 hierarchical fuzzy logic control. The problem is solved that the number of the rules increase exponentially with the number of variables involved. Experiments show that this approach is helpful and reliable especially to path planning of autonomous robot.","PeriodicalId":333889,"journal":{"name":"2008 International Conference on Internet Computing in Science and Engineering","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research on Hierarchial Fuzzy Behavior Learning of Autonomous Robot\",\"authors\":\"Ziying Zhang, Rubo Zhang, Xin Liu\",\"doi\":\"10.1109/ICICSE.2008.60\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the changing and dynamic unstructured environments of autonomous robot, this paper analyses these kinds of effects on robot in details and thus presents a local plan architecture based on hierarchical fuzzy logic to implement the basic navigation behaviors and the coordination between these behaviors to produce a type-2 hierarchical fuzzy logic control. The problem is solved that the number of the rules increase exponentially with the number of variables involved. Experiments show that this approach is helpful and reliable especially to path planning of autonomous robot.\",\"PeriodicalId\":333889,\"journal\":{\"name\":\"2008 International Conference on Internet Computing in Science and Engineering\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Internet Computing in Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSE.2008.60\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Internet Computing in Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSE.2008.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Hierarchial Fuzzy Behavior Learning of Autonomous Robot
Aiming at the changing and dynamic unstructured environments of autonomous robot, this paper analyses these kinds of effects on robot in details and thus presents a local plan architecture based on hierarchical fuzzy logic to implement the basic navigation behaviors and the coordination between these behaviors to produce a type-2 hierarchical fuzzy logic control. The problem is solved that the number of the rules increase exponentially with the number of variables involved. Experiments show that this approach is helpful and reliable especially to path planning of autonomous robot.
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