DocumentCode :
1614488
Title :
Vision-based precision vehicle localization in urban environments
Author :
Chuanxiang Li ; Bin Dai ; Tao Wu
Author_Institution :
Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2013
Firstpage :
599
Lastpage :
604
Abstract :
Global localization is a challenging problem in which autonomous vehicle has to estimate the self-position with respect to a priori map using perception results. In this paper we present a vision-based localization method for autonomous Vehicles in urban environment. The localization process consists of two stages: coarse localization using topological map and fine localization using metric map. The topological map represented by the holistic image feature provides coarse location, whereas localization from metric map is relatively slow, but more accurate. It is possible to integrate the two stages to make precise and reliable localization. The location system has been tested on autonomous vehicle in outdoor environment. The results show that our method is efficient and reliable.
Keywords :
SLAM (robots); mobile robots; position control; robot vision; a priori map; autonomous vehicle; coarse localization; fine localization; global localization; image feature; metric map; outdoor environment; self-position estimation; topological map; urban environment; vision-based precision vehicle localization; Current measurement; Feature extraction; Global Positioning System; Mobile robots; Reliability; Vectors; metric map; topological map; vision localization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
Type :
conf
DOI :
10.1109/CAC.2013.6775806
Filename :
6775806
Link To Document :
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