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An unmanned aerial vehicle (UAV) stabilization strategy based on computer vision and switching controllers is proposed. The main goal of this system is to perform tracking of a moving target on ground. The architecture implemented consists of a quadrotor equipped with an embedded camera which provides real-time video to a computer vision algorithm where images are processed. A vision-based estimator is proposed, which makes use of 2-dimensional images to compute the relative 3-dimensional position and translational velocity of the UAV with respect to the target. The proposed estimator provides the required states measurements to a micro-controller for stabilizing the vehicle during flight. The control strategy consists of switching controllers, which allows making decisions when the target is lost temporarily or when it is out of the camera’s field of view. Real time experiments are presented to demonstrate the performance of the target-tracking system proposed.  相似文献   
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In this paper, a vision based line tracking control strategy for mini-rotorcraft is presented. In order to estimate the 3-D position of the mini-rotorcraft over the trajectory a vanishing points technique is used. A dynamic model is derived employing the Newton–Euler approach and a nonlinear controller to stabilize, in closed-loop system, this mathematical model is proposed. To validate the theoretical results, a real-time embedded control system has been developed. The performance of the vision and control algorithms has been tested when the helicopter has tracked a line painted in a wall. The experimental results have shown the good behavior of the control laws.  相似文献   
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