Chao Liu, Gen Li, Yu Huang, Xiaolong Zhang, Yuanlong Xie, Jie Meng, Liquan Jiang
{"title":"Fast and Reliable Global Localization Using Reflector Landmarks","authors":"Chao Liu, Gen Li, Yu Huang, Xiaolong Zhang, Yuanlong Xie, Jie Meng, Liquan Jiang","doi":"10.1109/TENCON50793.2020.9293867","DOIUrl":null,"url":null,"abstract":"global localization is essential for pose initialization and pose recovery. However, for the lack of prior information, global localization is always unreliable and time consuming, especially in featureless and dynamic industry environment. To alleviate the negative influence of such environment, this paper uses reflector as landmarks. Then, several maps including labeled occupancy grid map and multi-resolution likelihood field are proposed to model the positions of landmarks as well as ordinary obstacles. Furthermore, a branch and bound method is employed to achieve fast global search based on those proposed maps. Through experiments in a real industry application, the reliability and efficiency of our proposed global localization method is verified.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE REGION 10 CONFERENCE (TENCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON50793.2020.9293867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
global localization is essential for pose initialization and pose recovery. However, for the lack of prior information, global localization is always unreliable and time consuming, especially in featureless and dynamic industry environment. To alleviate the negative influence of such environment, this paper uses reflector as landmarks. Then, several maps including labeled occupancy grid map and multi-resolution likelihood field are proposed to model the positions of landmarks as well as ordinary obstacles. Furthermore, a branch and bound method is employed to achieve fast global search based on those proposed maps. Through experiments in a real industry application, the reliability and efficiency of our proposed global localization method is verified.