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Visual Homing is the process by which a mobile robot moves to a Home position using only information extracted from visual data. The approach we present in this paper uses image keypoints (e.g. SIFT) extracted from omnidirectional images and matches the current set of keypoints with the set recorded at the Home location. In this paper, we first formulate three different visual homing problems using uncalibrated omnidirectional camera within the Image Based Visual Servoing (IBVS) framework; then we propose a novel simplified homing approach, which is inspired by IBVS, based only on the scale information of the SIFT features, with its computational cost linear to the number of features. This paper reports on the application of our method on a commonly cited indoor database where it outperforms other approaches. We also briefly present results on a real robot and allude on the integration into a topological navigation framework.
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