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Monocular Vision for Mobile Robot Localization and Autonomous Navigation

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This paper presents a new real-time localization system for a mobile robot. We show that autonomous navigation is possible in outdoor situation with the use of a single camera and natural landmarks. To do that, we use a three step approach. In a learning step, the robot is manually guided on a path and a video sequence is recorded with a front looking camera. Then a structure from motion algorithm is used to build a 3D map from this learning sequence. Finally in the navigation step, the robot uses this map to compute its localization in real-time and it follows the learning path or a slightly different path if desired. The vision algorithms used for map building and localization are first detailed. Then a large part of the paper is dedicated to the experimental evaluation of the accuracy and robustness of our algorithms based on experimental data collected during two years in various environments.

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Correspondence to Eric Royer.

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Royer, E., Lhuillier, M., Dhome, M. et al. Monocular Vision for Mobile Robot Localization and Autonomous Navigation. Int J Comput Vision 74, 237–260 (2007).

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