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Vision systems are used more and more in 'personal' robots interacting with humans, since semantic information about objects and places can be derived from the rich sensory information. Visual information is also used for building appearance based topological maps, which can be used for localization. In this paper we describe a system capable of using this appearance based topological map for navigation. The system is made robust by using the epipolar geometry and a planar floor constraint in computing the necessary heading information. Using this method the robot is able to drive robustly in a large environment. We tested the method on real data under varying environment conditions and compared performance with a human-controlled robot.
Booij et al. (Sun,) studied this question.