{"title":"机器人避障传感器布置与控制设计的协同进化方法","authors":"X. Wang, S.X. Yang, Weiren Shi, M. Meng","doi":"10.1109/ICIA.2004.1373331","DOIUrl":null,"url":null,"abstract":"This paper proposes a coevolution approach to optimal sensor placement and controller design for a mobile robot to facilitate its navigation and obstacle avoidance in an unknown environment. The mobile robots considered in this paper have flexible sensor and control structure. A genetic algorithm is developed to evolve the parameters of optimal sensor placement and fuzzy logic controller simultaneously. The preliminary results indicate that the proposed coevolution approach can lead to efficient robot sensor placement and control design.","PeriodicalId":297178,"journal":{"name":"International Conference on Information Acquisition, 2004. Proceedings.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A co-evolution approach to sensor placement and control design for robot obstacle avoidance\",\"authors\":\"X. Wang, S.X. Yang, Weiren Shi, M. Meng\",\"doi\":\"10.1109/ICIA.2004.1373331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a coevolution approach to optimal sensor placement and controller design for a mobile robot to facilitate its navigation and obstacle avoidance in an unknown environment. The mobile robots considered in this paper have flexible sensor and control structure. A genetic algorithm is developed to evolve the parameters of optimal sensor placement and fuzzy logic controller simultaneously. The preliminary results indicate that the proposed coevolution approach can lead to efficient robot sensor placement and control design.\",\"PeriodicalId\":297178,\"journal\":{\"name\":\"International Conference on Information Acquisition, 2004. Proceedings.\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Information Acquisition, 2004. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIA.2004.1373331\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Information Acquisition, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIA.2004.1373331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A co-evolution approach to sensor placement and control design for robot obstacle avoidance
This paper proposes a coevolution approach to optimal sensor placement and controller design for a mobile robot to facilitate its navigation and obstacle avoidance in an unknown environment. The mobile robots considered in this paper have flexible sensor and control structure. A genetic algorithm is developed to evolve the parameters of optimal sensor placement and fuzzy logic controller simultaneously. The preliminary results indicate that the proposed coevolution approach can lead to efficient robot sensor placement and control design.