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Robust Features Extraction for On-board Monocular-based Spacecraft Pose Acquisition

Capuano, Vincenzo and Alimo, Shahrouz Ryan and Ho, Andrew Q. and Chung, Soon-Jo (2019) Robust Features Extraction for On-board Monocular-based Spacecraft Pose Acquisition. In: AIAA Scitech 2019 Forum, 7-11 January 2019, San Diego, CA. http://resolver.caltech.edu/CaltechAUTHORS:20190109-132309708

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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.


Item Type:Conference or Workshop Item (Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.2514/6.2019-2005DOIArticle
ORCID:
AuthorORCID
Chung, Soon-Jo0000-0002-6657-3907
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.
Group:GALCIT
Funders:
Funding AgencyGrant Number
Swiss National Science Foundation (SNSF)UNSPECIFIED
NASA/JPL/CaltechUNSPECIFIED
Other Numbering System:
Other Numbering System NameOther Numbering System ID
AIAA Paper2019-2005
Record Number:CaltechAUTHORS:20190109-132309708
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190109-132309708
Official Citation:Robust Features Extraction for On-board Monocular-based Spacecraft Pose Acquisition. Vincenzo Capuano, Shahrouz Ryan Alimo, Andrew Q. Ho, and Soon-Jo Chung. AIAA Scitech 2019 Forum. San Diego, California.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92175
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:09 Jan 2019 22:36
Last Modified:09 Jan 2019 22:36

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