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.
Vision guided landing of an unmanned air vehicle
IEEE Conference on Decision and Control, 38 ; 4 ; 4143-4148
1999
6 Seiten, 12 Quellen
Conference paper
English
Visually guided landing of an unmanned aerial vehicle
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