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Imitation learning offers a promising path for robots to learn general-purpose behaviors, but traditionally has exhibited limited scalability due to high data supervision requirements and brittle generalization.
Inertial properties in robotic manipulation: An object-level framework
O. Khatib · 1995
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Long short-term memory
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D4rl: Datasets for deep data-driven reinforcement learning, 2020
J. Fu, A. Kumar, O. Nachum, G. Tucker, and S. Levine · 2004
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Robot learning from demonstration by constructing skill trees
G. Konidaris, S. Kuindersma, R. Grupen, and A. Barto · 2012
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Learning and generalization of complex tasks from unstructured demonstrations
S. Niekum, S. Osentoski, G. Konidaris, and A. G. Barto · 2012
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D. P. Kingma and M. Welling · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Deep spatial autoencoders for visuomotor learning
C. Finn, X. Y. Tan, Y. Duan, T. Darrell, S. Levine, and P. Abbeel · 2016
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The ”something something” video database for learning and evaluating visual common sense
R. Goyal, S. E. Kahou, V. Michalski, J. Materzyńska, S. Westphal, H. Kim, V. Haenel, I. Fruend, P. Yianilos, M. Mueller-Freitag, F. Hoppe, C. Thurau, I. Bax, and R. Memisevic · 2017
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DDCO: Discovery of deep continuous options for robot learning from demonstrations
S. Krishnan, R. Fox, I. Stoica, and K. Goldberg · 2017
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β \beta -vae: Learning basic visual concepts with a constrained variational framework
I. Higgins, L. Matthey, A. Pal, C. Burgess, X. Glorot, M. Botvinick, S. Mohamed, and A. Lerchner · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 2017
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Roboturk: A crowdsourcing platform for robotic skill learning through imitation
A. Mandlekar, Y. Zhu, A. Garg, J. Booher, M. Spero, A. Tung, J. Gao, J. Emmons, A. Gupta, E. Orbay, S. Savarese, and L. Fei-Fei · 2018
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Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
T. Zhang, Z. McCarthy, O. Jow, D. Lee, X. Chen, K. Goldberg, and P. Abbeel · 2018
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Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
A. Rajeswaran, V. Kumar, A. Gupta, G. Vezzani, J. Schulman, E. Todorov, and S. Levine · 2018
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Scaling egocentric vision: The epic-kitchens dataset
D. Damen, H. Doughty, G. M. Farinella, S. Fidler, A. Furnari, E. Kazakos, D. Moltisanti, J. Munro, T. Perrett, W. Price, and M. Wray · 2018
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Taco: Learning task decomposition via temporal alignment for control
K. Shiarlis, M. Wulfmeier, S. Salter, S. Whiteson, and I. Posner · 2018
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Learning manipulation graphs from demonstrations using multimodal sensory signals
Z. Su, O. Kroemer, G. E. Loeb, G. S. Sukhatme, and S. Schaal · 2018
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Time-contrastive networks: Self-supervised learning from video
P. Sermanet, C. Lynch, Y. Chebotar, J. Hsu, E. Jang, S. Schaal, and S. Levine · 2018
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Learning latent plans from play
C. Lynch, M. Khansari, T. Xiao, V. Kumar, J. Tompson, S. Levine, and P. Sermanet · 2019
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Robonet: Large-scale multi-robot learning
S. Dasari, F. Ebert, S. Tian, S. Nair, B. Bucher, K. Schmeckpeper, S. Singh, S. Levine, and C. Finn · 2019
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Compile: Compositional imitation learning and execution
T. Kipf, Y. Li, H. Dai, V. Zambaldi, A. Sanchez-Gonzalez, E. Grefenstette, P. Kohli, and P. Battaglia · 2019
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Transporter networks: Rearranging the visual world for robotic manipulation
Demonstration-guided reinforcement learning with learned skills
K. Pertsch, Y. Lee, Y. Wu, and J. J. Lim · 2021
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Error-aware imitation learning from teleoperation data for mobile manipulation
J. Wong, A. Tung, A. Kurenkov, A. Mandlekar, L. Fei-Fei, S. Savarese, and R. Martín-Martín · 2021
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Bc-z: Zero-shot task generalization with robotic imitation learning
E. Jang, A. Irpan, M. Khansari, D. Kappler, F. Ebert, C. Lynch, S. Levine, and C. Finn · 2021
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Cliport: What and where pathways for robotic manipulation
M. Shridhar, L. Manuelli, and D. Fox · 2021
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Language conditioned imitation learning over unstructured data
C. Lynch and P. Sermanet · 2021
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Skid raw: Skill discovery from raw trajectories
D. Tanneberg, K. Ploeger, E. Rueckert, and J. Peters · 2021
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Accelerating reinforcement learning with learned skill priors
K. Pertsch, Y. Lee, and J. J. Lim · 2020
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Iris: Implicit reinforcement without interaction at scale for learning control from offline robot manipulation data
A. Mandlekar, F. Ramos, B. Boots, S. Savarese, L. Fei-Fei, A. Garg, and D. Fox · 2020
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Scaling data-driven robotics with reward sketching and batch reinforcement learning
S. Cabi, S. Gómez Colmenarejo, A. Novikov, K. Konyushkova, S. Reed, R. Jeong, K. Zolna, Y. Aytar, D. Budden, M. Vecerik, et al · 2020
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Learning robot skills with temporal variational inference
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Laser: Learning a latent action space for efficient reinforcement learning
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Calvin - a benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks
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Offline reinforcement learning with implicit q-learning
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