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This work introduces the Spacecraft Pose Network (SPN) for on-board estimation of the pose, i.e., the relative position and attitude, of a known non-cooperative spacecraft using monocular vision.
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S. Sharma and S. D’Amico, “Comparative assessment of techniques for initial pose estimation using monocular vision,” Acta Astronautica
2015
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H. Su, C. R. Qi, Y. Li, and L. J. Guibas, “Render for CNN: Viewpoint estimation in images using CNNs trained with rendered 3D model views,” Proceedings of the IEEE International Conference on Computer Vision
2015
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2015
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A. Kendall, M. Grimes, and R. Cipolla, “PoseNet: A convolutional network for real-time 6-dof camera relocalization,” Proceedings of the IEEE International Conference on Computer Vision
2015
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S. Sharma, J. Ventura, and S. D’Amico, “Robust Model-Based Monocular Pose Initialization for Noncooperative Spacecraft Rendezvous,” Journal of Spacecraft and Rockets
2018
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V. Capuano, G. Cuciniello, V. Pesce, R. Opromolla, S. Sarno, M. Lavagna, M. Grassi, F. Corraro, G. Capuano, P. Tabacco, F. Meta, M. L. Battagliere, and T. Alberto, “VINAG: A highly integrated system for autonomous on-board absolute and relative spacecraft navigation,” The 4S Symposium 2018
2018
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2018
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S. Sharma, C. Beierle, and S. D’Amico, “Pose Estimation for Non-Cooperative Spacecraft Rendezvous Using Convolutional Neural Networks,” 2018 IEEE Aerospace Conference
2018
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2015
Cited alongside, same era.
J. L. Forshaw, G. S. Aglietti, N. Navarathinam, H. Kadhem, T. Salmon, A. Pisseloup, E. Joffre, T. Chabot, I. Retat, R. Axthelm, S. Barraclough, A. Ratcliffe, C. Bernal, F. Chaumette, A. Pollini, and W. H. Steyn, “RemoveDEBRIS: An in-orbit active debris removal demonstration mission,” Acta Astronautica
2016
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B. B. Reed, R. C. Smith, B. J. Naasz, J. F. Pellegrino, and C. E. Bacon, “The Restore-L Servicing Mission,” AIAA Space Forum
2016
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M. Avilés, D. Mora, M. Canetri, and P. Colmenarejo, “A Complete IP-based Navigation Solution for the Approach and Capture of Active Debris,” 67th International Astronautical Congress
2016
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S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” Advances In Neural Information Processing Systems
2016
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K. Bessho, K. Date, M. Hayashi, A. Ikeda, T. Imai, H. Inoue, Y. Kumagai, T. Miyakawa, H. Murata, T. Ohno, A. Okuyama, R. Oyama, Y. Sasaki, Y. Shimazu, K. Shimoji, Y. Sumida, M. Suzuki, H. Taniguchi, H. Tsuchiyama, D. Uesawa, H. Yokota, and R. Yoshida, “An Introduction to Himawari-8/9- Japan’s New-Generation Geostationary Meteorological Satellites,” Journal of the Meteorological Society of Japan
2016
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S. Sharma and S. D’Amico, “Reduced-Dynamics Pose Estimation for Non-Cooperative Spacecraft Rendezvous using Monocular Vision,” Proceedings of the 40th Annual AAS Rocky Mountain Section Guidance and Control Conference
2017
Cited alongside, same era.
S. Sharma, C. Beierle, and S. D’Amico, “Towards Pose Determination for Non-Cooperative Spacecraft using Convolutional Neural Networks,” Proceedings of the 1st IAA Conference on Space Situational Awareness (ICSSA)
2017
Cited alongside, same era.
Y. Xiang, T. Schmidt, V. Narayanan, and D. Fox, “PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes,” 2017, 10.15607/RSS.2018.XIV.019
2018
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2018
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PhD thesis, Massachusetts Institute of Technology, 2018
J. Wu, Robotic Object Pose Estimation with Deep Neural Networks · 2018
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2018
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C. Beierle and Simone D’Amico, “Variable Magnification Optical Stimulator for Training and Validation of Spaceborne Vision-Based Navigation,” Journal of Spacecraft and Rockets (In Print)
2018
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S. Sharma, A. Koenig, and J. Sullivan, “Verification of Light-box Devices for Earth Albedo Simulation,” https://damicos.people.stanford.edu/sites/g/files/sbiybj2226/f/tn2016_sharmakoenigsullivan.pdf
2018
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2018
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European Space Agency, “Kelvins - ESA’s Advanced Concepts Competition Website,” https://kelvins.esa.int · 2019
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Space Rendezvous Laboratory, Stanford University, “SLAB - Multi-satellite systems for unrivaled space science and exploration,” https://slab.stanford.edu · 2019
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H. Daumé, “Frustratingly Easy Domain Adaptation,” ArXiv:0907.1815v1
2062
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