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Imitation learning is a promising approach for learning robot policies with user-provided data.
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2019
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2020
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I. El Rassi and J.-M. El Rassi, “A review of haptic feedback in tele-operated robotic surgery,”
2020
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M. Sakr, M. Freeman, H. M. Van der Loos, and E. Croft, “Training human teacher to improve robot learning from demonstration: A pilot study on kinesthetic teaching,” in
2020
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H. Liu, S. Nasiriany, L. Zhang, Z. Bao, and Y. Zhu, “Robot learning on the job: Human-in-the-loop autonomy and learning during deployment,”
2023
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2023
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2023
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Y. Qin, W. Yang, B. Huang, K. Van Wyk, H. Su, X. Wang, Y.-W. Chao, and D. Fox, “Anyteleop: A general vision-based dexterous robot arm-hand teleoperation system,” in
2023
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S. Belkhale, Y. Cui, and D. Sadigh, “Data quality in imitation learning,”
2024
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2021
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Y. Cui, P. Koppol, H. Admoni, S. Niekum, R. Simmons, A. Steinfeld, and T. Fitzgerald, “Understanding the relationship between interactions and outcomes in human-in-the-loop machine learning,” in
2021
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F. E. Jedrzej Orbik, “Oculus reader: Robotic teleoperation interface,” 2021, accessed: YYYY-MM-DD. [Online]. Available:
2021
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Y. Zhu, P. Stone, and Y. Zhu, “Bottom-up skill discovery from unsegmented demonstrations for long-horizon robot manipulation,”
2022
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K. Gandhi, S. Karamcheti, M. Liao, and D. Sadigh, “Eliciting compatible demonstrations for multi-human imitation learning,” in
2022
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2023
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Cited in the paper.
J. Hejna, C. A. Bhateja, Y. Jiang, K. Pertsch, and D. Sadigh, “Remix: Optimizing data mixtures for large scale imitation learning,” in
2024
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S. Yang, M. Liu, Y. Qin, D. Runyu, L. Jialong, X. Cheng, R. Yang, S. Yi, and X. Wang, “Ace: A cross-platfrom visual-exoskeletons for low-cost dexterous teleoperation,”
2024
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X. Jiang, P. Mattes, X. Jia, N. Schreiber, G. Neumann, and R. Lioutikov, “A comprehensive user study on augmented reality-based data collection interfaces for robot learning,” in
2024
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C. Chi, Z. Xu, C. Pan, E. Cousineau, B. Burchfiel, S. Feng, R. Tedrake, and S. Song, “Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots,” in
2024
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R. Ding, Y. Qin, J. Zhu, C. Jia, S. Yang, R. Yang, X. Qi, and X. Wang, “Bunny-visionpro: Real-time bimanual dexterous teleoperation for imitation learning,” 2024
2024
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J. Gao, A. Xie, T. Xiao, C. Finn, and D. Sadigh, “Efficient data collection for robotic manipulation via compositional generalization,” in
2024
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