{"title":"基于图像分析的离散自定位方法","authors":"Włodzimierz Kasprzak, W. Szynkiewicz","doi":"10.1109/ROMOCO.2002.1177134","DOIUrl":null,"url":null,"abstract":"A method for discrete self-localization of an autonomous mobile system was proposed. One of its many possible implementations was designed, that uses a camera subsystem, which delivers sensor information about the environment reduced to an n-elementary measurement vector. Three different algorithms of image analysis were proposed and implemented. The self-localization approach with three different image sub-systems was tested by computer simulations on different natural and synthetic scenes.","PeriodicalId":213750,"journal":{"name":"Proceedings of the Third International Workshop on Robot Motion and Control, 2002. RoMoCo '02.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A method for discrete self-localization using image analysis\",\"authors\":\"Włodzimierz Kasprzak, W. Szynkiewicz\",\"doi\":\"10.1109/ROMOCO.2002.1177134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method for discrete self-localization of an autonomous mobile system was proposed. One of its many possible implementations was designed, that uses a camera subsystem, which delivers sensor information about the environment reduced to an n-elementary measurement vector. Three different algorithms of image analysis were proposed and implemented. The self-localization approach with three different image sub-systems was tested by computer simulations on different natural and synthetic scenes.\",\"PeriodicalId\":213750,\"journal\":{\"name\":\"Proceedings of the Third International Workshop on Robot Motion and Control, 2002. RoMoCo '02.\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third International Workshop on Robot Motion and Control, 2002. RoMoCo '02.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROMOCO.2002.1177134\",\"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 of the Third International Workshop on Robot Motion and Control, 2002. RoMoCo '02.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMOCO.2002.1177134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A method for discrete self-localization using image analysis
A method for discrete self-localization of an autonomous mobile system was proposed. One of its many possible implementations was designed, that uses a camera subsystem, which delivers sensor information about the environment reduced to an n-elementary measurement vector. Three different algorithms of image analysis were proposed and implemented. The self-localization approach with three different image sub-systems was tested by computer simulations on different natural and synthetic scenes.
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