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Machine Vision and Applications
Published in: Machine Vision and Applications 1/2021

01-02-2021 | Original Paper

Vision-based relative pose determination of cooperative spacecraft in neutral buoyancy environment

Authors: Guohua Jia, Chaoqing Min, Kedian Wang, Zhanxia Zhu

Published in: Machine Vision and Applications | Issue 1/2021

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Abstract

Neutral buoyancy systems simulate the microgravity environment by taking advantage of buoyancy forces of water to offset the gravity of test bodies. Functional verification of space robots in neutral buoyancy system is of great importance for ground tests. The relative pose determination of a spacecraft plays an essential role in the on-orbit operation of space robots. In order to meet the requirement of on-orbit operation ground verification for space robots, this paper develops a vision-based system for determining the relative pose of cooperative spacecraft in neutral buoyancy environment. Cooperative markers and underwater binocular vision system are designed for the pose determination, and a cooperative spacecraft model is built. A detection and recognition method based on the topological characteristic is proposed for the cooperative marker. An underwater imaging model of binocular camera is established, and its refraction parameters are calibrated. The marker points are measured with an underwater binocular 3D measurement algorithm. Furthermore, the pose of cooperative spacecraft is determined using axisymmetric plane feature points. Additionally, the stable and reliable pose and velocity are obtained after the data are further processed with a Kalman filter. Finally, the experiments are carried out and the experimental results show that the proposed system can achieve a stable and reliable high-precision relative pose determination for cooperative spacecraft in neutral buoyancy environment.
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Appendix
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Metadata
Title
Vision-based relative pose determination of cooperative spacecraft in neutral buoyancy environment
Authors
Guohua Jia
Chaoqing Min
Kedian Wang
Zhanxia Zhu
Publication date
01-02-2021
Publisher
Springer Berlin Heidelberg
Published in
Machine Vision and Applications / Issue 1/2021
Print ISSN: 0932-8092
Electronic ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-020-01137-7

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