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While imitation learning methods have seen a resurgent interest for robotic manipulation, the well-known problem of compounding errors continues to afflict behavioral cloning (BC).
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S. Schaal · 1999
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K. Hsiao and T. Lozano-Perez · 2006
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B. D. Argall, S. Chernova, M. Veloso, and B. Browning · 2009
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Efficient reductions for imitation learning
S. Ross and D. Bagnell · 2010
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S. Ross, G. Gordon, and D. Bagnell · 2011
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M. Welling and Y. W. Teh · 2011
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Mujoco: A physics engine for model-based control
E. Todorov, T. Erez, and Y. Tassa · 2012
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D. P. Kingma and M. Welling · 2013
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Learning structured output representation using deep conditional generative models
K. Sohn, H. Lee, and X. Yan · 2015
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Shiv: Reducing supervisor burden in dagger using support vectors for efficient learning from demonstrations in high dimensional state spaces
M. Laskey, S. Staszak, W. Y.-S. Hsieh, J. Mahler, F. T. Pokorny, A. D. Dragan, and K. Goldberg · 2016
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Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching
A. Zeng, S. Song, K.-T. Yu, E. Donlon, F. R. Hogan, M. Bauza, D. Ma, O. Taylor, M. Liu, E. Romo, N. Fazeli, F. Alet, N. C. Dafle, R. Holladay, I. Morona, P. Q. Nair, D. Green, I. Taylor, W. Liu, T. Funkhouser, and A. Rodriguez · 2017
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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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Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach
D. Morrison, P. Corke, and J. Leitner · 2018
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Learning synergies between pushing and grasping with self-supervised deep reinforcement learning
A. Zeng, S. Song, S. Welker, J. Lee, A. Rodriguez, and T. Funkhouser · 2018
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Self-supervised correspondence in visuomotor policy learning
P. Florence, L. Manuelli, and R. Tedrake · 2019
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Tossingbot: Learning to throw arbitrary objects with residual physics
A. Zeng, S. Song, J. Lee, A. Rodriguez, and T. Funkhouser · 2020
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Spatial action maps for mobile manipulation
J. Wu, X. Sun, A. Zeng, S. Song, J. Lee, S. Rusinkiewicz, and T. Funkhouser · 2020
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Form2fit: Learning shape priors for generalizable assembly from disassembly
Q-attention: Enabling efficient learning for vision-based robotic manipulation
S. James and A. J. Davison · 2022
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Behavior transformers: Cloning k k modes with one stone
N. M. Shafiullah, Z. Cui, A. A. Altanzaya, and L. Pinto · 2022
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Rt-1: Robotics transformer for real-world control at scale
A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, J. Dabis, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, J. Hsu, et al · 2022
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Viola: Imitation learning for vision-based manipulation with object proposal priors
Y. Zhu, A. Joshi, P. Stone, and Y. Zhu · 2022
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Implicit behavioral cloning
P. Florence, C. Lynch, A. Zeng, O. A. Ramirez, A. Wahid, L. Downs, A. Wong, J. Lee, I. Mordatch, and J. Tompson · 2022
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K. Zakka, A. Zeng, J. Lee, and S. Song · 2020
Cited alongside, same era.
Tossingbot: Learning to throw arbitrary objects with residual physics
A. Zeng, S. Song, J. Lee, A. Rodriguez, and T. Funkhouser · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
Cited alongside, same era.
What matters in learning from offline human demonstrations for robot manipulation
A. Mandlekar, D. Xu, J. Wong, S. Nasiriany, C. Wang, R. Kulkarni, L. Fei-Fei, S. Savarese, Y. Zhu, and R. Martín-Martín · 2021
Cited alongside, same era.
Transporter networks: Rearranging the visual world for robotic manipulation
A. Zeng, P. Florence, J. Tompson, S. Welker, J. Chien, M. Attarian, T. Armstrong, I. Krasin, D. Duong, V. Sindhwani, et al · 2021
Cited alongside, same era.
Generalization through hand-eye coordination: An action space for learning spatially-invariant visuomotor control
C. Wang, R. Wang, A. Mandlekar, L. Fei-Fei, S. Savarese, and D. Xu · 2021
Cited alongside, same era.
Coarse-to-fine imitation learning: Robot manipulation from a single demonstration
E. Johns · 2021
Cited alongside, same era.
Cliport: What and where pathways for robotic manipulation
M. Shridhar, L. Manuelli, and D. Fox · 2022
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Seil: Simulation-augmented equivariant imitation learning
M. Jia, D. Wang, G. Su, D. Klee, X. Zhu, R. Walters, and R. Platt · 2022
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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 · 2022
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Perceiver-actor: A multi-task transformer for robotic manipulation
M. Shridhar, L. Manuelli, and D. Fox · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
T. Z. Zhao, V. Kumar, S. Levine, and C. Finn · 2023
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Nerf in the palm of your hand: Corrective augmentation for robotics via novel-view synthesis
A. Zhou, M. J. Kim, L. Wang, P. Florence, and C. Finn · 2023
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Hydra: Hybrid robot actions for imitation learning
S. Belkhale, Y. Cui, and D. Sadigh · 2023
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