Reference : CubeSat-CDT: A Cross-Domain Dataset for 6-DoF Trajectory Estimation of a Symmetric Sp...
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/52237
CubeSat-CDT: A Cross-Domain Dataset for 6-DoF Trajectory Estimation of a Symmetric Spacecraft
English
Mohamed Ali, Mohamed Adel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
Rathinam, Arunkumar mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
Gaudilliere, Vincent mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
Ortiz Del Castillo, Miguel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
Aouada, Djamila mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
2022
Proceedings of the 17th European Conference on Computer Vision Workshops (ECCVW 2022)
Yes
International
European Conference on Computer Vision Workshops
October 23-27, 2022
[en] Computer Vision ; Deep Learning ; Space Situational Awareness
[en] This paper introduces a new cross-domain dataset, CubeSat-
CDT, that includes 21 trajectories of a real CubeSat acquired in a labora-
tory setup, combined with 65 trajectories generated using two rendering
engines – i.e. Unity and Blender. The three data sources incorporate the
same 1U CubeSat and share the same camera intrinsic parameters. In ad-
dition, we conduct experiments to show the characteristics of the dataset
using a novel and efficient spacecraft trajectory estimation method, that
leverages the information provided from the three data domains. Given a
video input of a target spacecraft, the proposed end-to-end approach re-
lies on a Temporal Convolutional Network that enforces the inter-frame
coherence of the estimated 6-Degree-of-Freedom spacecraft poses. The
pipeline is decomposed into two stages; first, spatial features are ex-
tracted from each frame in parallel; second, these features are lifted to
the space of camera poses while preserving temporal information. Our re-
sults highlight the importance of addressing the domain gap problem to
propose reliable solutions for close-range autonomous relative navigation
between spacecrafts. Since the nature of the data used during training
impacts directly the performance of the final solution, the CubeSat-CDT
dataset is provided to advance research into this direction.
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Computer Vision Imaging & Machine Intelligence (CVI²)
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/52237
FnR ; FNR14755859 > Djamila Aouada > MEET-A > Multi-modal Fusion Of Electro-optical Sensors For Spacecraft Pose Estimation Towards Autonomous In-orbit Operations > 01/01/2021 > 31/12/2023 > 2020

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