Visual topological SLAM and global localization

Abstract : Visual localization and mapping for mobile robots has been achieved with a large variety of methods. Among them, topological navigation using vision has the advantage of offering a scalable representation, and of relying on a common and affordable sensor. In previous work, we developed such an incremental and real-time topological mapping and localization solution, without using any metrical information, and by relying on a Bayesian visual loop-closure detection algorithm. In this paper, we propose an extension of this work by integrating metrical information from robot odometry in the topological map, so as to obtain a globally consistent environment model. Also, we demonstrate the performance of our system on the global localization task, where the robot has to determine its position in a map acquired beforehand.
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Adrien Angeli, Stéphane Doncieux, Jean-Arcady Meyer, David Filliat. Visual topological SLAM and global localization. International Conference on Robotics and Automation (ICRA), 2009, Japan. pp.4300 - 4305, ⟨10.1109/ROBOT.2009.5152501⟩. ⟨hal-00652601⟩

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