The European V-Charge project seeks to develop fully automated valet parking and charging of electric vehicles using only low-cost sensors. One of the challenges is to implement robust visual localization using only cameras and stock vehicle sensors. We integrated four monocular, wide-angle, fisheye cameras on a consumer car and implemented a mapping and localization pipeline. Visual features and odometry are combined to build and localize against a keyframe-based three dimensional map. We report results for the first stage of the project, based on two months worth of data acquired under varying conditions, with the objective of localizing against a map created offline.
Evaluation of fisheye-camera based visual multi-session localization in a real-world scenario
2013-06-01
1311180 byte
Conference paper
Electronic Resource
English
EVALUATION OF FISHEYE-CAMERA BASED VISUAL MULTI-SESSION LOCALIZATION IN A REAL-WORLD SCENARIO
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