DocumentCode
2595498
Title
Kalman filters predictive steps comparison for vehicle localization
Author
Mourllion, Benjamin ; Gruyer, Dominique ; Lambert, Alain ; Glaser, Sébastien
Author_Institution
LIVIC, INRETS/LCPC, Versailles Satory, France
fYear
2005
fDate
2-6 Aug. 2005
Firstpage
565
Lastpage
571
Abstract
The aim of this paper is to perform a comparison among several different Kalman filters algorithms designed for nonlinear systems. After presenting the most popular of them and showing its limitations, we introduce some new Kalman filters in order to compare them in the vehicle localization context. This comparison is based on the sole use of their predictive steps that corresponds to the worst case that it can occur in vehicle localization (corrective data are unavailable).
Keywords
Kalman filters; nonlinear control systems; position control; vehicles; Kalman filters predictive steps; extended Kalman filters; nonlinear systems; vehicle localization; Algorithm design and analysis; Filters; Gaussian noise; Jacobian matrices; Linear systems; Mobile robots; Noise measurement; Nonlinear systems; State estimation; Vehicles; DD1; DD2; EKF; UKF; vehicle localization;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on
Print_ISBN
0-7803-8912-3
Type
conf
DOI
10.1109/IROS.2005.1545151
Filename
1545151
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