{"title":"不同环境下的地标匹配","authors":"A. Carbonaro, P. Zingaretti","doi":"10.1109/EURBOT.1997.633621","DOIUrl":null,"url":null,"abstract":"A system for landmark tracking by a template matching approach is described. Route following based on landmarks may require many models to cover all different situations, so a genetic algorithm learning technique is used to adapt modelling parameters to environmental conditions (lighting, shadows, reflexes, etc.) during the tracking. In addition, the mobile robot self-localisation is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence analysis in the 3D position estimation. The experimental results show that the tracking robustness is improved when the adaptive template matching is used for landmark tracking.","PeriodicalId":129683,"journal":{"name":"Proceedings Second EUROMICRO Workshop on Advanced Mobile Robots","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Landmark matching in a varying environment\",\"authors\":\"A. Carbonaro, P. Zingaretti\",\"doi\":\"10.1109/EURBOT.1997.633621\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A system for landmark tracking by a template matching approach is described. Route following based on landmarks may require many models to cover all different situations, so a genetic algorithm learning technique is used to adapt modelling parameters to environmental conditions (lighting, shadows, reflexes, etc.) during the tracking. In addition, the mobile robot self-localisation is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence analysis in the 3D position estimation. The experimental results show that the tracking robustness is improved when the adaptive template matching is used for landmark tracking.\",\"PeriodicalId\":129683,\"journal\":{\"name\":\"Proceedings Second EUROMICRO Workshop on Advanced Mobile Robots\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Second EUROMICRO Workshop on Advanced Mobile Robots\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EURBOT.1997.633621\",\"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 Second EUROMICRO Workshop on Advanced Mobile Robots","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURBOT.1997.633621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A system for landmark tracking by a template matching approach is described. Route following based on landmarks may require many models to cover all different situations, so a genetic algorithm learning technique is used to adapt modelling parameters to environmental conditions (lighting, shadows, reflexes, etc.) during the tracking. In addition, the mobile robot self-localisation is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence analysis in the 3D position estimation. The experimental results show that the tracking robustness is improved when the adaptive template matching is used for landmark tracking.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
