Share Email Print
cover

Proceedings Paper

Visual navigation of the UAVs on the basis of 3D natural landmarks
Author(s): Simon Karpenko; Ivan Konovalenko; Alexander Miller; Boris Miller; Dmitry Nikolaev
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 8 December 2015
PDF: 10 pages
Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98751I (8 December 2015); doi: 10.1117/12.2228793
Show Author Affiliations
Simon Karpenko, Institute for Information Transmission Problems (Russian Federation)
Ivan Konovalenko, Institute for Information Transmission Problems (Russian Federation)
Alexander Miller, Institute for Information Transmission Problems (Russian Federation)
Boris Miller, Institute for Information Transmission Problems (Russian Federation)
Dmitry Nikolaev, Institute for Information Transmission Problems (Russian Federation)


Published in SPIE Proceedings Vol. 9875:
Eighth International Conference on Machine Vision (ICMV 2015)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev, Editor(s)

© SPIE. Terms of Use
Back to Top