{"title":"基于建筑轮廓的二维在线地图在城市环境中的车辆定位","authors":"Jonghwi Kim, Yonghoon Cho, Jinwhan Kim","doi":"10.1109/URAI.2018.8441821","DOIUrl":null,"url":null,"abstract":"We discuss GPS-free localization in urban areas using a lidar and a 2D online map with building outlines. To achieve this, the boundaries of buildings extracted from the reference map are matched to 3D point cloud data provided by the lidar. The normalized mutual information between them is maximized. The matching result is used as a measurement and combined with odometry and inertial sensor measurements using an extended Kalman filter. The proposed method has been implemented and verified through an experiment with a mobile robot.","PeriodicalId":347727,"journal":{"name":"2018 15th International Conference on Ubiquitous Robots (UR)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Vehicle Localization in Urban Environment Using a 2D Online Map with Building Outlines\",\"authors\":\"Jonghwi Kim, Yonghoon Cho, Jinwhan Kim\",\"doi\":\"10.1109/URAI.2018.8441821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We discuss GPS-free localization in urban areas using a lidar and a 2D online map with building outlines. To achieve this, the boundaries of buildings extracted from the reference map are matched to 3D point cloud data provided by the lidar. The normalized mutual information between them is maximized. The matching result is used as a measurement and combined with odometry and inertial sensor measurements using an extended Kalman filter. The proposed method has been implemented and verified through an experiment with a mobile robot.\",\"PeriodicalId\":347727,\"journal\":{\"name\":\"2018 15th International Conference on Ubiquitous Robots (UR)\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th International Conference on Ubiquitous Robots (UR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URAI.2018.8441821\",\"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 15th International Conference on Ubiquitous Robots (UR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2018.8441821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vehicle Localization in Urban Environment Using a 2D Online Map with Building Outlines
We discuss GPS-free localization in urban areas using a lidar and a 2D online map with building outlines. To achieve this, the boundaries of buildings extracted from the reference map are matched to 3D point cloud data provided by the lidar. The normalized mutual information between them is maximized. The matching result is used as a measurement and combined with odometry and inertial sensor measurements using an extended Kalman filter. The proposed method has been implemented and verified through an experiment with a mobile robot.
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