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Dexterous manipulation with a multi-finger hand is one of the most challenging problems in robotics.
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D. Rus · 1999
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R. Rubinstein · 1999
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A. M. Okamura, N. Smaby, and M. R. Cutkosky · 2000
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Algorithms for inverse reinforcement learning
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M. R. Dogar and S. S. Srinivasa · 2010
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Synthesizing grasp configurations with specified contact regions
C. Rosales, L. Ros, J. M. Porta, and R. Suárez · 2011
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S. Andrews and P. G. Kry · 2013
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Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
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Challenges in representation learning: A report on three machine learning contests
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Y. Bai and C. K. Liu · 2014
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Shapenet: An information-rich 3d model repository
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J. Schulman, S. Levine, P. Abbeel, M. Jordan, and P. Moritz · 2015
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Learning dexterous manipulation for a soft robotic hand from human demonstrations
A. Gupta, C. Eppner, S. Levine, and P. Abbeel · 2016
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Optimal control with learned local models: Application to dexterous manipulation
V. Kumar, E. Todorov, and S. Levine · 2016
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Generative adversarial imitation learning
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Benchmarking deep reinforcement learning for continuous control
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Reinforcement learning with unsupervised auxiliary tasks, 2016
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Learning robust rewards with adversarial inverse reinforcement learning
J. Fu, K. Luo, and S. Levine · 2017
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Third-person imitation learning
B. C. Stadie, P. Abbeel, and I. Sutskever · 2017
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Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards
M. Večerík, T. Hester, J. Scholz, F. Wang, O. Pietquin, B. Piot, N. Heess, T. Rothörl, T. Lampe, and M. Riedmiller · 2017
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Embodied hands: Modeling and capturing hands and bodies together
J. Romero, D. Tzionas, and M. J. Black · 2017
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Learning dexterous in-hand manipulation
OpenAI, M. Andrychowicz, B. Baker, M. Chociej, R. Józefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, J. Schneider, S. Sidor, J. Tobin, P. Welinder, L. Weng, and W. Zaremba · 2018
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A geometric perspective on visual imitation learning
J. Jin, L. Petrich, M. Dehghan, and M. Jagersand · 2020
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Motion reasoning for goal-based imitation learning
D.-A. Huang, Y.-W. Chao, C. Paxton, X. Deng, L. Fei-Fei, J. C. Niebles, A. Garg, and D. Fox · 2020
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Visual imitation made easy
S. Young, D. Gandhi, S. Tulsiani, A. Gupta, P. Abbeel, and L. Pinto · 2020
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Curl: Contrastive unsupervised representations for reinforcement learning
A. Srinivas, M. Laskin, and P. Abbeel · 2020
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Data-efficient reinforcement learning with self-predictive representations
M. Schwarzer, A. Anand, R. Goel, R. D. Hjelm, A. Courville, and P. Bachman · 2020
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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
Cited alongside, same era.
Path planning for within-hand manipulation over learned representations of safe states
B. Calli, A. Kimmel, K. Hang, K. Bekris, and A. Dollar · 2018
Cited alongside, same era.
Behavioral cloning from observation
F. Torabi, G. Warnell, and P. Stone · 2018
Cited alongside, same era.
Playing hard exploration games by watching youtube
Y. Aytar, T. Pfaff, D. Budden, T. Paine, Z. Wang, and N. de Freitas · 2018
Cited alongside, same era.
Generative adversarial imitation from observation
F. Torabi, G. Warnell, and P. Stone · 2018
Cited alongside, same era.
Solving rubik’s cube with a robot hand
OpenAI, I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, J. Schneider, N. Tezak, J. Tworek, P. Welinder, L. Weng, Q. Yuan, W. Zaremba, and L. Zhang · 2019
Cited alongside, same era.
Dexterous manipulation with deep reinforcement learning: Efficient, general, and low-cost
H. Zhu, A. Gupta, A. Rajeswaran, S. Levine, and V. Kumar · 2019
Cited alongside, same era.
Grasping field: Learning implicit representations for human grasps
K. Karunratanakul, J. Yang, Y. Zhang, M. J. Black, K. Muandet, and S. Tang · 2020
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Ganhand: Predicting human grasp affordances in multi-object scenes
E. Corona, A. Pumarola, G. Alenya, F. Moreno-Noguer, and G. Rogez · 2020
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State-only imitation learning for dexterous manipulation
I. Radosavovic, X. Wang, L. Pinto, and J. Malik · 2021
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Dexmv: Imitation learning for dexterous manipulation from human videos
Y. Qin, Y.-H. Wu, S. Liu, H. Jiang, R. Yang, Y. Fu, and X. Wang · 2021
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Hand-object contact consistency reasoning for human grasps generation
H. Jiang, S. Liu, J. Wang, and X. Wang · 2021
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Generalization in dexterous manipulation via geometry-aware multi-task learning
W. Huang, I. Mordatch, P. Abbeel, and D. Pathak · 2021
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Learning dexterous grasping with object-centric visual affordances
P. Mandikal and K. Grauman · 2021
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Decoupling representation learning from reinforcement learning
A. Stooke, K. Lee, P. Abbeel, and M. Laskin · 2021
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Self-supervised policy adaptation during deployment
N. Hansen, R. Jangir, Y. Sun, G. Alenyà, P. Abbeel, A. A. Efros, L. Pinto, and X. Wang · 2021
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Generalization in reinforcement learning by soft data augmentation
N. Hansen and X. Wang · 2021
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Maniskill: Generalizable manipulation skill benchmark with large-scale demonstrations
T. Mu, Z. Ling, F. Xiang, D. Yang, X. Li, S. Tao, Z. Huang, Z. Jia, and H. Su · 2021
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T. Liu, Z. Liu, Z. Jiao, Y. Zhu, and S.-C. Zhu · 2021
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Manipnet: neural manipulation synthesis with a hand-object spatial representation
H. Zhang, Y. Ye, T. Shiratori, and T. Komura · 2021
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Y. Qin, H. Su, and X. Wang · 2022
Closest in time.
A system for general in-hand object re-orientation
T. Chen, J. Xu, and P. Agrawal · 2022
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Dexterous imitation made easy: A learning-based framework for efficient dexterous manipulation
S. P. Arunachalam, S. Silwal, B. Evans, and L. Pinto · 2022
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Robotic telekinesis: Learning a robotic hand imitator by watching humans on youtube
A. Sivakumar, K. Shaw, and D. Pathak · 2022
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