DocumentCode
1894269
Title
On line mapping and global positioning for autonomous driving in urban environment based on evidential SLAM
Author
Trehard, Guillaume ; Pollard, Evangeline ; Bradai, Benazouz ; Nashashibi, Fawzi
Author_Institution
RITS Team, INRIA, Rocquencourt, France
fYear
2015
fDate
June 28 2015-July 1 2015
Firstpage
814
Lastpage
819
Abstract
Locate a vehicle in an urban environment remains a challenge for the autonomous driving community. By fusing information from a LIDAR, a Global Navigation by Satellite System (GNSS) and the vehicle odometry, this article proposes a solution based on evidential grids and a particle filter to map the static environment and simultaneously estimate the position in a global reference at a high rate and without any prior knowledge.
Keywords
Global Positioning System; SLAM (robots); mobile robots; position control; road vehicles; robot vision; GNSS; Global Navigation by Satellite system; Global Positioning System; SLAM; autonomous driving; online mapping; position estimation; urban environment; vehicle odometry; Approximation algorithms; Global Positioning System; Laser radar; Mathematical model; Simultaneous localization and mapping; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium (IV), 2015 IEEE
Conference_Location
Seoul
Type
conf
DOI
10.1109/IVS.2015.7225785
Filename
7225785
Link To Document