{"title":"基于核磁共振距离的自动驾驶汽车定位与映射","authors":"Guangjing Li, H. Bao, Bo Wang, Tao Wu","doi":"10.1109/CIS.2017.00023","DOIUrl":null,"url":null,"abstract":"Accurate locating is an important task for autonomous vehicles' safely driving. In order to realize the precise locating autonomous vehicles without Global Positioning System(GPS) signal, a Kernelized Rényi Distance(KRD) based simultaneous localization and mapping(SLAM) algorithm is proposed in this paper. In our Algorithm, pose estimation are computed by optimizing KRD between two groups of laser point(in odometry process) or between laser points and the local map(in mapping process). The experimental results indicate that the proposed algorithm can accurately locate autonomous vehicle and build the traveled environment map.","PeriodicalId":304958,"journal":{"name":"2017 13th International Conference on Computational Intelligence and Security (CIS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Kernelised Rényi Distance for Localization and Mapping of Autonomous Vehicle\",\"authors\":\"Guangjing Li, H. Bao, Bo Wang, Tao Wu\",\"doi\":\"10.1109/CIS.2017.00023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurate locating is an important task for autonomous vehicles' safely driving. In order to realize the precise locating autonomous vehicles without Global Positioning System(GPS) signal, a Kernelized Rényi Distance(KRD) based simultaneous localization and mapping(SLAM) algorithm is proposed in this paper. In our Algorithm, pose estimation are computed by optimizing KRD between two groups of laser point(in odometry process) or between laser points and the local map(in mapping process). The experimental results indicate that the proposed algorithm can accurately locate autonomous vehicle and build the traveled environment map.\",\"PeriodicalId\":304958,\"journal\":{\"name\":\"2017 13th International Conference on Computational Intelligence and Security (CIS)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th International Conference on Computational Intelligence and Security (CIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2017.00023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th International Conference on Computational Intelligence and Security (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2017.00023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Kernelised Rényi Distance for Localization and Mapping of Autonomous Vehicle
Accurate locating is an important task for autonomous vehicles' safely driving. In order to realize the precise locating autonomous vehicles without Global Positioning System(GPS) signal, a Kernelized Rényi Distance(KRD) based simultaneous localization and mapping(SLAM) algorithm is proposed in this paper. In our Algorithm, pose estimation are computed by optimizing KRD between two groups of laser point(in odometry process) or between laser points and the local map(in mapping process). The experimental results indicate that the proposed algorithm can accurately locate autonomous vehicle and build the traveled environment map.