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One fundamental difficulty in robotic learning is the sim-real gap problem.
Robust wide-baseline stereo from maximally stable extremal regions
Jiri Matas, Ondrej Chum, Martin Urban, and Tomás Pajdla · 2004
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Efficient reductions for imitation learning
Stephane Ross and Drew Bagnell · 2010
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A reduction of imitation learning and structured prediction to no-regret online learning
Stephane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards
Jeffrey Mahler, Florian T Pokorny, Brian Hou, Melrose Roderick, Michael Laskey, Mathieu Aubry, Kai Kohlhoff, Torsten Kröger, James Kuffner, and Ken Goldberg · 2016
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Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
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Reinforcement learning through asynchronous advantage actor-critic on a gpu
Mohammad Babaeizadeh, Iuri Frosio, Stephen Tyree, Jason Clemons, and Jan Kautz · 2017
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Tadanobu Inoue, Subhajit Chaudhury, Giovanni De Magistris, and Sakyasingha Dasgupta · 2017
Cited alongside, same era.
Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task
Stephen James, Andrew J. Davison, and Edward Johns · 2017
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End-to-end learning of semantic grasping
Eric Jang, Sudheendra Vijayanarasimhan, Peter Pastor, Julian Ibarz, and Sergey Levine · 2017
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Deep reinforcement learning, decision making, and control
Sergey Levine and Chelsea Finn · 2017
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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, and Deirdre Quillen · 2017
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Sim-to-real robot learning from pixels with progressive nets
Andrei A. Rusu, Matej Večerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, and Raia Hadsell · 2017
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
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Gplac: Generalizing vision-based robotic skills using weakly labeled images
Avi Singh, Larry Yang, and Sergey Levine · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Joshua Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
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Deep object-centric representations for generalizable robot learning
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Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, and Ken Goldberg · 2017
Cited alongside, same era.
Data-efficient deep reinforcement learning for dexterous manipulation
Ivaylo Popov, Nicolas Heess, Timothy Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerik, Thomas Lampe, Yuval Tassa, Tom Erez, and Martin Riedmiller · 2017
Cited alongside, same era.
Learning task-oriented grasping for tool manipulation from simulated self-supervision
Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, and Silvio Savarese
Cited in the paper.
Coline Devin, Pieter Abbeel, Trevor Darrell, and Sergey Levine · 2018
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Multi-task domain adaptation for deep learning of instance grasping from simulation
Kuan Fang, Yunfei Bai, Stefan Hinterstoisser, Silvio Savarese, and Mrinal Kalakrishnan · 2018
Later among the works it cites.
Sim-to-real transfer of robotic control with dynamics randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, and Pieter Abbeel · 2018
Later among the works it cites.