In this paper, we study the problem of using computer vision as a sensor to control the landing of an unmanned air vehicle (UAV). The vision problem we address is a special case of the general ego-motion estimation problem due to the fact that all feature points lie on a plane. We propose a new geometric estimation scheme for solving the differential version of the planar ego-motion estimation problem. The algorithm is computationally inexpensive and amenable for real-time implementation. We present a performance evaluation of the algorithm under different levels of image measurement noise and camera motions relative to the landing pad. We also present a full dynamic model of a UAV, discuss a nonlinear controller based on differential flatness, and show through simulation that the vision guided UAV performs stable landing maneuvers even under large levels of image measurement noise.


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    Title :

    Vision guided landing of an unmanned air vehicle


    Contributors:
    Shakernia, O. (author) / Yi Ma (author) / Koo, T.J. (author) / Hespanha, J. (author) / Sastry, S.S. (author)

    Published in:

    Publication date :

    1999


    Size :

    6 Seiten, 12 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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