DocumentCode :
262949
Title :
Real-time vehicle localization by using a top-down process
Author :
Aynaud, Claude ; Bernay-Angeletti, Coralie ; Chapuis, Roland ; Aufrere, Romuald ; Debain, Christophe ; Karam, Nadir
Author_Institution :
Inst. Pascal, UBP, Aubiere, France
fYear :
2014
fDate :
7-10 July 2014
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, a localization system for a mobile robot is proposed, using a top-down multi-sensorial approach and exploiting a map of the environment. Nowadays the wide development of maps make relevant localization approachesable to use such maps. A crucial point of all localization systems is the way of the data provided by different sensors are fused. The proposed approach is based on a Bayesian network able to select the best feature to detect in the map with the best sensor in order to reach both precision and integrity of the robot localization. This process is working in real time and was validated in simulated and real environments.
Keywords :
Kalman filters; belief networks; mobile robots; path planning; sensor fusion; Bayesian network; maps development; mobile robot localization system; real-time vehicle localization; top-down multi-sensorial approach; Accuracy; Bayes methods; Detectors; Robots; Uncertainty; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2014 17th International Conference on
Conference_Location :
Salamanca
Type :
conf
Filename :
6916083
Link To Document :
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