8 December 2015 Visual navigation of the UAVs on the basis of 3D natural landmarks
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Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 98751I (2015) https://doi.org/10.1117/12.2228793
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain
Abstract
This work considers the tracking of the UAV (unmanned aviation vehicle) on the basis of onboard observations of natural landmarks including azimuth and elevation angles. It is assumed that UAV's cameras are able to capture the angular position of reference points and to measure the angles of the sight line. Such measurements involve the real position of UAV in implicit form, and therefore some of nonlinear filters such as Extended Kalman filter (EKF) or others must be used in order to implement these measurements for UAV control. Recently it was shown that modified pseudomeasurement method may be used to control UAV on the basis of the observation of reference points assigned along the UAV path in advance. However, the use of such set of points needs the cumbersome recognition procedure with the huge volume of on-board memory. The natural landmarks serving as such reference points which may be determined on-line can significantly reduce the on-board memory and the computational difficulties. The principal difference of this work is the usage of the 3D reference points coordinates which permits to determine the position of the UAV more precisely and thereby to guide along the path with higher accuracy which is extremely important for successful performance of the autonomous missions. The article suggests the new RANSAC for ISOMETRY algorithm and the use of recently developed estimation and control algorithms for tracking of given reference path under external perturbation and noised angular measurements.
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Simon Karpenko, Simon Karpenko, Ivan Konovalenko, Ivan Konovalenko, Alexander Miller, Alexander Miller, Boris Miller, Boris Miller, Dmitry Nikolaev, Dmitry Nikolaev, } "Visual navigation of the UAVs on the basis of 3D natural landmarks", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98751I (8 December 2015); doi: 10.1117/12.2228793; https://doi.org/10.1117/12.2228793
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