Dynamic estimation of homography transformations on the special linear group for visual servo control

In the last decade, many vision-based robot controllers have been designed using Cartesian information encoded in the homography transformation that links two images of a planar object. For any approach, the performance of the closed-loop system depends on the quality of the homography estimates obtained. In this paper, we exploit the special linear Lie-group structure of the set of all homographies to develop a dynamic observer to estimate homographies online. The resulting estimates are effective and can be used to improve closed-loop response of several visual servoing algorithms.

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