{"title":"三个智能控制传感的例子","authors":"P. Mowforth, E. Grant","doi":"10.1109/ISIC.1988.65417","DOIUrl":null,"url":null,"abstract":"Three studies that broadly relate to the issue of sensing for intelligent robotic are reviewed. The first involves the data-driven construction of a dynamic world model for use in mobile robot navigation. The second demonstrates a machine learned, rule-based controller for a pole and cart problem. The third, for which results are provided, is a sensory integration exercise involving a vision and a taction system embedded in a multirobot work-cell.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Three examples of sensing for intelligent control\",\"authors\":\"P. Mowforth, E. Grant\",\"doi\":\"10.1109/ISIC.1988.65417\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Three studies that broadly relate to the issue of sensing for intelligent robotic are reviewed. The first involves the data-driven construction of a dynamic world model for use in mobile robot navigation. The second demonstrates a machine learned, rule-based controller for a pole and cart problem. The third, for which results are provided, is a sensory integration exercise involving a vision and a taction system embedded in a multirobot work-cell.<<ETX>>\",\"PeriodicalId\":155616,\"journal\":{\"name\":\"Proceedings IEEE International Symposium on Intelligent Control 1988\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Symposium on Intelligent Control 1988\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.1988.65417\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE International Symposium on Intelligent Control 1988","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.1988.65417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Three studies that broadly relate to the issue of sensing for intelligent robotic are reviewed. The first involves the data-driven construction of a dynamic world model for use in mobile robot navigation. The second demonstrates a machine learned, rule-based controller for a pole and cart problem. The third, for which results are provided, is a sensory integration exercise involving a vision and a taction system embedded in a multirobot work-cell.<>
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