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Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain
Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain
Faculty Publications
This paper demonstrates a feasible method for using a deep neural network as a sensor to estimate the attitude of a flying vehicle using only flight video. A dataset of still images and associated gravity vectors was collected and used to perform supervised learning. The network builds on a previously trained network and was trained to be able to approximate the attitude of the camera with an average error of about 8 degrees. Flight test video was recorded and processed with a relatively simple visual odometry method. The aircraft attitude is then estimated with the visual odometry as the state …