{"title":"Backing up GPS in urban areas using a scanning laser","authors":"M. Jabbour, P. Bonnifait","doi":"10.1109/PLANS.2008.4570058","DOIUrl":null,"url":null,"abstract":"This paper studies the use of lidar for the egolocalization of car-like vehicles in conjunction with GPS. We consider a laser scanner installed at the front of a vehicle that detects both sides of the road. We present a method that fuses the lidar information to improve the localization process by providing additional exteroceptive information and by rejecting bad GPS fixes. The strategy is inspired by a SLAM paradigm and is efficient if the vehicle navigates often in the same area. We present the different main stages of such a strategy: lidar data processing, map data representation, and augmented Kalman filtering scheme. Finally, experimental results are reported to illustrate the performance of this approach.","PeriodicalId":446381,"journal":{"name":"2008 IEEE/ION Position, Location and Navigation Symposium","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE/ION Position, Location and Navigation Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PLANS.2008.4570058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This paper studies the use of lidar for the egolocalization of car-like vehicles in conjunction with GPS. We consider a laser scanner installed at the front of a vehicle that detects both sides of the road. We present a method that fuses the lidar information to improve the localization process by providing additional exteroceptive information and by rejecting bad GPS fixes. The strategy is inspired by a SLAM paradigm and is efficient if the vehicle navigates often in the same area. We present the different main stages of such a strategy: lidar data processing, map data representation, and augmented Kalman filtering scheme. Finally, experimental results are reported to illustrate the performance of this approach.