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Vision guided landing of an unmanned air vehicle

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5 Author(s)
Shakernia, O. ; Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA ; Yi Ma ; Koo, T.J. ; Hespanha, J.
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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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Decision and Control, 1999. Proceedings of the 38th IEEE Conference on  (Volume:4 )

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