Spacecraft Pose Estimation Dataset of a 3U CubeSat using Unreal Engine (SPEED-UE-Cube)
Abstract/Contents
- Abstract
SPEED-UE-Cube is a synthetic image dataset that was created by the Space Rendezvous Laboratory (SLAB) using Unreal Engine 5. The dataset is intended for training and evaluating the performance of supervised machine learning models for monocular pose estimation of a noncooperative spacecraft. It models spaceborne imagery of a 3U CubeSat and consists of two subsets: a training dataset of 30,000 images with a 80/20 training/validation split, and a trajectory dataset of 1,186 images that depict a rendezvous scenario between the CubeSat and a servicer spacecraft. All images are accompanied with pose labels that provide the relative position and orientation of the target CubeSat. The dataset is released under a CC-BY-4.0 license and is therefore available for commercial use.
The dataset is hosted by MathWorks and can be downloaded at the following link. Please note that using the link will automatically begin downloading the dataset (44 GB):
https://ssd.mathworks.com/supportfiles/computer_vision_specialization/Data/SPEEDUECubeDataset.zip
Description
| Type of resource | Dataset, still image |
|---|---|
| Date created | May 1, 2023 |
| Date modified | January 17, 2024; February 1, 2024 |
| Publication date | January 17, 2024; January 17, 2024 |
Creators/Contributors
| Author | Park, Tae Ha |
|---|---|
| Author | Ahmed, Zahra |
| Author | Bhattacharjee, Abhijit |
| Author | Fazel-Rezai, Reza |
| Author | Graves, Russell |
| Author | Saarela, Ossi |
| Author | Teramoto, Reece |
| Author | Vemulapalli, Kautilya |
| Author | D'Amico, Simone |
Subjects
| Subject | Satellites |
|---|---|
| Subject | Pose Estimation |
| Subject | Machine learning |
| Subject | CubeSat |
| Subject | Unreal Engine |
| Genre | Data |
| Genre | Image |
| Genre | Data sets |
| Genre | Dataset |
Bibliographic information
| Related item |
|
|---|---|
| Location | https://purl.stanford.edu/hw812wb1641 |
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 4.0 International license (CC BY).
Preferred citation
- Preferred citation
- Park, T.H., Ahmed, Z., Bhattacharjee, A., Razel-Rezai, R., Graves, R., Saarela, O., Teramoto, R., Vemulapalli, K., and D'Amico, S. (2024). Spacecraft Pose Estimation Dataset of a 3U CubeSat using Unreal Engine (SPEED-UE-Cube). Available at https://purl.stanford.edu/hw812wb1641.
Collection
Stanford Research Data
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