Year: 2017
Type: article
Abstract: Introduction. Autonomous rendezvous and docking is an important technological capability that enables various spacecraft missions. It requires the real-time relative pose estimation i.e. determination of the position and attitude of a target object relative to a chaser. The usage of techniques based on optical measurement has certain advantages at close range phases of docking.The purpose of the paper is to create a computer vision system, that estimates position and attitude of the target relative to the chaser.To develop the design of a computer vision system and suited mathematical methods.To use a new learning-based method, which can be implemented for the real-time execution with limited computing power.Methods.A non-standard approach to solving the problem was used.A combination of image processing techniques, machine learning, decision trees and piecewise linear approximation of functions were used.The tool of informative features computed by images was essentially used.Results.A two-stage algorithm, which involves training the computer vision system to recognize the attitude and position of the target in a changing lighting environment was developed.The calculation of the camera parameters was carried out to ensure a given accuracy of the solution of the problem. Conclusion.It was shown that the informative features can be used to create a highperformance on-board system for estimating relative attitude and position.Implementation of the proposed algorithm allows to create a competitive device for docking in space.
Authors: S. Melnychuk, V. Gubarev, N. Salnikov
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2772006305