Incremental vision-based topological SLAM

Abstract : In robotics, appearance-based topological map building consists in infering the topology of the environment explored by a robot from its sensor measurements. In this paper, we propose a vision-based framework that considers this data association problem from a loop-closure detection perspective in order to correctly assign each measurement to its location. Our approach relies on the visual bag of words paradigm to represent the images and on a discrete Bayes filter to compute the probability of loop-closure. We demonstrate the efficiency of our solution by incremental and real-time consistent map building in an indoor environment and under strong perceptual aliasing conditions using a single monocular wide-angle camera
Mots-clés : robotique vision navigation
Type de document :
Communication dans un congrès
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008. IROS 2008, Sep 2008, Nice, France. pp.1031 - 1036, 2008, 〈10.1109/IROS.2008.4650675〉
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Adrien Angeli, Stéphane Doncieux, Jean-Arcady Meyer, David Filliat. Incremental vision-based topological SLAM. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008. IROS 2008, Sep 2008, Nice, France. pp.1031 - 1036, 2008, 〈10.1109/IROS.2008.4650675〉. 〈hal-00647374〉

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