{"title":"Experimental research of probabilistic localization of service robots using range image data and indoor GPS system","authors":"Hyeyeon Chang, Jong-suk Choi, Munsang Kim","doi":"10.1109/ETFA.2006.355414","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed a probabilistic localization of service robot using laser scanner and indoor GPS system. This scheme is a sample based algorithm as an application of Monte Carlo localization. Samples are scattered by referring to odometry data and position data of indoor GPS system. And those are evaluated by map-matching method using laser sensor and distance error matching using indoor GPS system. We are able to get more robust localization results by using these processes, even though the floor condition is deteriorated and there are many or huge obstacles And it is possible that remove errors which are caused when the robot is blocked by unexpected obstacles for a long time. Experimental results demonstrate the evaluation of the robustness of our algorithm fusing range image sensor and indoor GPS system data.","PeriodicalId":431393,"journal":{"name":"2006 IEEE Conference on Emerging Technologies and Factory Automation","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Emerging Technologies and Factory Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2006.355414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper, we proposed a probabilistic localization of service robot using laser scanner and indoor GPS system. This scheme is a sample based algorithm as an application of Monte Carlo localization. Samples are scattered by referring to odometry data and position data of indoor GPS system. And those are evaluated by map-matching method using laser sensor and distance error matching using indoor GPS system. We are able to get more robust localization results by using these processes, even though the floor condition is deteriorated and there are many or huge obstacles And it is possible that remove errors which are caused when the robot is blocked by unexpected obstacles for a long time. Experimental results demonstrate the evaluation of the robustness of our algorithm fusing range image sensor and indoor GPS system data.