Stochastic control of UAV on the basis of robust filtering of 3D natural landmarks observations

This work considers the tracking of the UAV (unmanned aviation vehicle) on the basis of on-board observations of natural landmarks including azimuth and elevation angles. It is assumed that either UAV’s cameras are able to capture the angular position of reference point 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 guide the UAV along the path with varying altitude which is extremely important for successful performance of some autonomous missions. One more novelty of this approach is the usage of robust RANSAC taking into account the UAV motion model. The article suggests the estimation and control algorithm for tracking given reference path under external perturbation and noised angular measurements. This research was conducted at the IITP RAS and suppurted by the Russian Scientific Fund grant #14-50-00150.