Spacecraft Pose Estimation Dataset (SPEED)

Abstract/Contents

Abstract

This repository contains Spacecraft PosE Estimation Dataset (SPEED), which is used to train and evaluate the performance of deep learning models for pose estimation of noncooperative spacecraft. SPEED consists of synthetic as well as actual camera images of a mock-up of the Tango spacecraft from the PRISMA mission. The synthetic images are created by fusing OpenGL-based renderings of the spacecraft’s 3D model with actual images of the Earth captured by the Himawari-8 meteorological satellite. The actual camera images are created using a 7 degrees-of-freedom robotic arm, which positions and orients a vision-based sensor with respect to a full-scale mock-up of the Tango spacecraft. Custom illumination devices simulate the Earth albedo and Sun light with high fidelity to emulate the illumination conditions present in space. SPEED was used in the international competition for spacecraft pose estimation co-hosted by the Advanced Concepts Team of the European Space Agency and the Space Rendezvous Laboratory of Stanford University.

Description

Type of resource	Dataset
Date created	February 1, 2019
Date modified	September 8, 2022
Publication date	September 2, 2022

Creators/Contributors

Compiler	Sharma, Sumant	https://orcid.org/0000-0002-6186-3761 (unverified)
Author	Park, Tae Ha	https://orcid.org/0000-0001-7938-9976 (unverified)
Advisor	D'Amico, Simone

Subjects

Subject	Satellites
Subject	Pose Estimation
Subject	Computer vision
Subject	Machine learning
Genre	Data
Genre	Data sets
Genre	Dataset

Bibliographic information

Related item	Title Kelvins Pose Estimation Challenge Preferred citation Kisantal, M., Sharma, S., Park, T. H., Izzo, D., Märtens, M., and D'Amico, S. Satellite Pose Estimation Challenge: Dataset, Competition Design and Results. ArXiv preprint arXiv:1911.02050 (2019). Preferred citation Sharma, S. and D'Amico, S. Pose Estimation for Non-Cooperative Spacecraft Rendezvous using Neural Networks. 2019 AAS/AIAA Astrodynamics Specialist Conference, Ka'anapali, Maui, HI, January 13-17 (2019).
DOI	https://doi.org/10.25740/dz692fn7184
Location	https://purl.stanford.edu/dz692fn7184

Access conditions

Use and reproduction

User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.

License

This work is licensed under a Creative Commons Attribution Non Commercial Share Alike 4.0 International license (CC BY-NC-SA).

Preferred citation

Preferred citation

Sharma, Sumant and Park, Tae Ha and D'Amico, Simone. (2019). Spacecraft Pose Estimation Dataset (SPEED). Stanford Digital Repository. Available at: https://purl.stanford.edu/dz692fn7184. https://doi.org/10.25740/dz692fn7184

Collection

Stanford Research Data

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Contact information

Contact

sumant28@gmail.com

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