Robust Features Extraction for On-board Monocular-based Spacecraft Pose Acquisition
Abstract
This paper presents the design, implementation, and validation of a robust feature extraction architecture for real-time on-board monocular vision-based pose initialization of a target spacecraft in application to on-orbit servicing and formation flying. The proposed computer vision algorithm is designed to detect the most significant features of an uncooperative target spacecraft in a sequence of two-dimensional input images that are collected on board the chaser spacecraft. A novel approach based on the fusion of multiple and parallel processing streams is proposed to filter a minimum number of extracted true point features, even in case of unfavourable illumination conditions and in presence of Earth in the background. These are then combined into relevant polyline structures that characterize the true geometrical shape of the target spacecraft.
Additional Information
© 2019 AIAA. AIAA Paper 2019-2005. The first author would like to thank the Swiss National Science Foundation (SNSF), that supported him for this research. The authors also gratefully acknowledge partial funding from Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA) in support of this work. The authors thank F. Y. Hadaegh, A. Stoica, and M. Wolf. In addition, the authors would like to thank Techno System Development s.r.l. that kindly made the images of Tango available for this research study.Attached Files
Accepted Version - SciTech_2019_paper_Capuano.pdf
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Additional details
- Eprint ID
- 92175
- Resolver ID
- CaltechAUTHORS:20190109-132309708
- Swiss National Science Foundation (SNSF)
- NASA/JPL/Caltech
- Created
-
2019-01-09Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field
- Caltech groups
- GALCIT
- Other Numbering System Name
- AIAA Paper
- Other Numbering System Identifier
- 2019-2005