{"title":"基于扩展卡尔曼滤波和Aruco标记的检测机器人视觉定位","authors":"Jingxiang Zheng, S. Bi, Bo Cao, Dongsheng Yang","doi":"10.1109/ROBIO.2018.8664777","DOIUrl":null,"url":null,"abstract":"This paper investigates a localization technology based on Aruco Markers for substation inspection robot. Extended Kalman Filter(EKF) algorithm is used to fuse odometer information and camera measurement data from detection of Aruco markers. The experiment results show that the localization problem can be solved by EKF localization based on Aruco markers efficiently. The localization algorithm can provide the inspection robot with relatively accurate position information and shield the impact of the dynamic environment.","PeriodicalId":417415,"journal":{"name":"2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Visual Localization of Inspection Robot Using Extended Kalman Filter and Aruco Markers\",\"authors\":\"Jingxiang Zheng, S. Bi, Bo Cao, Dongsheng Yang\",\"doi\":\"10.1109/ROBIO.2018.8664777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates a localization technology based on Aruco Markers for substation inspection robot. Extended Kalman Filter(EKF) algorithm is used to fuse odometer information and camera measurement data from detection of Aruco markers. The experiment results show that the localization problem can be solved by EKF localization based on Aruco markers efficiently. The localization algorithm can provide the inspection robot with relatively accurate position information and shield the impact of the dynamic environment.\",\"PeriodicalId\":417415,\"journal\":{\"name\":\"2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROBIO.2018.8664777\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2018.8664777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visual Localization of Inspection Robot Using Extended Kalman Filter and Aruco Markers
This paper investigates a localization technology based on Aruco Markers for substation inspection robot. Extended Kalman Filter(EKF) algorithm is used to fuse odometer information and camera measurement data from detection of Aruco markers. The experiment results show that the localization problem can be solved by EKF localization based on Aruco markers efficiently. The localization algorithm can provide the inspection robot with relatively accurate position information and shield the impact of the dynamic environment.
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