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Employing a teleoperation system for gathering demonstrations offers the potential for more efficient learning of robot manipulation.
J. Kofman, X. Wu, T. J. Luu, and S. Verma, “Teleoperation of a robot manipulator using a vision-based human-robot interface,” IEEE transactions on industrial electronics , vol. 52, no. 5, pp. 1206–1219, 2005
2005
Earlier work this paper cites.
F. Weichert, D. Bachmann, B. Rudak, and D. Fisseler, “Analysis of the accuracy and robustness of the leap motion controller,” Sensors , vol. 13, no. 5, pp. 6380–6393, 2013
2013
Earlier work this paper cites.
A. D. Dragan and S. S. Srinivasa, “A policy-blending formalism for shared control,” The International Journal of Robotics Research , vol. 32, no. 7, pp. 790–805, 2013
2013
Earlier work this paper cites.
T. Schmidt, R. A. Newcombe, and D. Fox, “Dart: Dense articulated real-time tracking.” in Robotics: Science and systems , vol. 2, no. 1. Berkeley, CA, 2014, pp. 1–9
2014
Earlier work this paper cites.
S. Javdani, S. S. Srinivasa, and J. A. Bagnell, “Shared autonomy via hindsight optimization,” Robotics science and systems: online proceedings , 2015
2015
Earlier work this paper cites.
D. Sadigh, S. S. Sastry, S. A. Seshia, and A. Dragan, “Information gathering actions over human internal state,” in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2016, pp. 66–73
2016
Earlier work this paper cites.
H. Liu, X. Xie, M. Millar, M. Edmonds, F. Gao, Y. Zhu, V. J. Santos, B. Rothrock, and S.-C. Zhu, “A glove-based system for studying hand-object manipulation via joint pose and force sensing,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2017, pp. 6617–6624
2017
Earlier work this paper cites.
J. I. Lipton, A. J. Fay, and D. Rus, “Baxter’s homunculus: Virtual reality spaces for teleoperation in manufacturing,” IEEE Robotics and Automation Letters , vol. 3, no. 1, pp. 179–186, 2017
2017
Earlier work this paper cites.
K. Muelling, A. Venkatraman, J.-S. Valois, J. E. Downey, J. Weiss, S. Javdani, M. Hebert, A. B. Schwartz, J. L. Collinger, and J. A. Bagnell, “Autonomy infused teleoperation with application to brain computer interface controlled manipulation,” Autonomous Robots , vol. 41, pp. 1401–1422, 2017
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
A. Mandlekar, Y. Zhu, A. Garg, J. Booher, M. Spero, A. Tung, J. Gao, J. Emmons, A. Gupta, E. Orbay et al. , “Roboturk: A crowdsourcing platform for robotic skill learning through imitation,” in Conference on Robot Learning . PMLR, 2018, pp. 879–893
2018
Earlier work this paper cites.
S. Javdani, H. Admoni, S. Pellegrinelli, S. S. Srinivasa, and J. A. Bagnell, “Shared autonomy via hindsight optimization for teleoperation and teaming,” The International Journal of Robotics Research , vol. 37, no. 7, pp. 717–742, 2018
2018
Earlier work this paper cites.
Z. Gharaybeh, H. Chizeck, and A. Stewart, Telerobotic control in virtual reality . IEEE, 2019
2019
Earlier work this paper cites.
H. Liu, Z. Zhang, X. Xie, Y. Zhu, Y. Liu, Y. Wang, and S.-C. Zhu, “High-fidelity grasping in virtual reality using a glove-based system,” in 2019 international conference on robotics and automation (ICRA) . IEEE, 2019, pp. 5180–5186
2019
Earlier work this paper cites.
D. Antotsiou, G. Garcia-Hernando, and T.-K. Kim, “Task-oriented hand motion retargeting for dexterous manipulation imitation,” in Computer Vision–ECCV 2018 Workshops: Munich, Germany, September 8-14, 2018, Proceedings, Part VI 15 . Springer, 2019, pp. 287–301
2019
Cited alongside, same era.
S. Li, X. Ma, H. Liang, M. Görner, P. Ruppel, B. Fang, F. Sun, and J. Zhang, “Vision-based teleoperation of shadow dexterous hand using end-to-end deep neural network,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 416–422
2019
Cited alongside, same era.
A. Handa, K. Van Wyk, W. Yang, J. Liang, Y.-W. Chao, Q. Wan, S. Birchfield, N. Ratliff, and D. Fox, “Dexpilot: Vision-based teleoperation of dexterous robotic hand-arm system,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 9164–9170
2020
Cited alongside, same era.
D. P. Losey, H. J. Jeon, M. Li, K. Srinivasan, A. Mandlekar, A. Garg, J. Bohg, and D. Sadigh, “Learning latent actions to control assistive robots,” Autonomous robots , vol. 46, no. 1, pp. 115–147, 2022
2022
Later among the works it cites.
M. Janner, Y. Du, J. B. Tenenbaum, and S. Levine, “Planning with diffusion for flexible behavior synthesis,” 2022
2022
Later among the works it cites.
C. Luo, “Understanding diffusion models: A unified perspective,” 2022
2022
Later among the works it cites.
S. P. Arunachalam, I. Güzey, S. Chintala, and L. Pinto, “Holo-dex: Teaching dexterity with immersive mixed reality,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 5962–5969
2023
Later among the works it cites.
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2020
Cited alongside, same era.
2020
Cited alongside, same era.
J. Ho, A. Jain, and P. Abbeel, “Denoising diffusion probabilistic models,” Advances in neural information processing systems , vol. 33, pp. 6840–6851, 2020
2020
Cited alongside, same era.
2021
Cited alongside, same era.
J. Lv, W. Xu, L. Yang, S. Qian, C. Mao, and C. Lu, “Handtailor: Towards high-precision monocular 3d hand recovery,” British Machine Vision Conference (BMVC) , 2021
2021
Cited alongside, same era.
Y. Rong, T. Shiratori, and H. Joo, “Frankmocap: A monocular 3d whole-body pose estimation system via regression and integration,” in IEEE International Conference on Computer Vision Workshops , 2021
2021
Cited alongside, same era.
2021
Cited alongside, same era.
C. Mower, J. Moura, and S. Vijayakumar, “Skill-based shared control,” in Robotics: Science and Systems XVII . The Robotics: Science and Systems Foundation, Jul. 2021, robotics: Science and Systems 2021, R:SS 2021 ; Conference date: 12-07-2021 Through 16-07-2021. [Online]. Available: https://roboticsconference.org/
2021
Cited alongside, same era.
P. Florence, C. Lynch, A. Zeng, O. A. Ramirez, A. Wahid, L. Downs, A. Wong, J. Lee, I. Mordatch, and J. Tompson, “Implicit behavioral cloning,” in Conference on Robot Learning . PMLR, 2022, pp. 158–168
2022
Cited alongside, same era.
2023
Later among the works it cites.
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song, “Diffusion policy: Visuomotor policy learning via action diffusion,” 2023
2023
Later among the works it cites.
2023
Later among the works it cites.
H. R. Walke, K. Black, T. Z. Zhao, Q. Vuong, C. Zheng, P. Hansen-Estruch, A. W. He, V. Myers, M. J. Kim, M. Du et al. , “Bridgedata v2: A dataset for robot learning at scale,” in Conference on Robot Learning . PMLR, 2023, pp. 1723–1736
2023
Later among the works it cites.
2023
Later among the works it cites.
A. Ajay, Y. Du, A. Gupta, J. Tenenbaum, T. Jaakkola, and P. Agrawal, “Is conditional generative modeling all you need for decision-making?” 2023
2023
Later among the works it cites.
M. Xu, Z. Xu, C. Chi, M. Veloso, and S. Song, “Xskill: Cross embodiment skill discovery,” 2023
2023
Later among the works it cites.
T. Yoneda, L. Sun, G. Yang, B. C. Stadie, and M. R. Walter, “To the noise and back: Diffusion for shared autonomy,” in Robotics: Science and Systems XIX, Daegu, Republic of Korea, July 10-14, 2023 , 2023
2023
Later among the works it cites.
H. Fang, H.-S. Fang, Y. Wang, J. Ren, J. Chen, R. Zhang, W. Wang, and C. Lu, “Airexo: Low-cost exoskeletons for learning whole-arm manipulation in the wild,” in 2024 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2024, pp. 15 031–15 038
2024
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