Air combat maneuvering pdf4/15/2024 The linear and angular velocity signals being computed may be noisy as such, we also investigate a nonlinear observer to filter the possible noisy signal and test this observer on the equations of motion of a rigid body undergoing rotations and translations. Without access to real data taken from a camera undergoing a known motion, we test the algorithms on random synthetic data and compare the results to the initial known linear and angular velocity. The two methods discussed are the continuous eight-point algorithm and a direct minimization of a cost function. The only information needed is the pixel position vectors, the image motion vectors, and the speed of the UAV. We describe two methods used to recover the linear and angular velocity that the UAV (camera) underwent between the two camera frames. Using two consecutive images, image motion vectors are computed for a given collection of pixel position vectors. Image processing seeks to determine the °ow of the image in the image plane. We instead investigate several of the `post processing of the image' issues. With the use of a camera, one part of this process is image processing, but it is not discussed here. We seek autonomous control and obstacle avoidance using a sequence of images from a camera. Of the many techniques used for UAV control, this research is vision based. In this work, we investigate just a few of the many computational issues involved in achieving autonomous control of unmanned air vehicles (UAVs).
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