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Long-horizon contact-rich tasks are challenging to learn with reinforcement learning, due to ineffective exploration of high-dimensional state spaces with sparse rewards.
Contact-invariant optimization for hand manipulation
Igor Mordatch, Zoran Popović, and Emanuel Todorov · 2012
Earlier work this paper cites.
Yale-cmu-berkeley dataset for robotic manipulation research
Berk Calli, Arjun Singh, James Bruce, Aaron Walsman, Kurt Konolige, Siddhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar · 2017
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Learning dexterous in-hand manipulation
OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Józefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, Jonas Schneider, Szymon Sidor, Josh Tobin, Peter Welinder, Lilian Weng, and Wojciech Zaremba · 2020
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Learning quadrupedal locomotion over challenging terrain
Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun, and Marco Hutter · 2020
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A system for general in-hand object re-orientation
Tao Chen, Jie Xu, and Pulkit Agrawal · 2021
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Learning high-speed flight in the wild
Antonio Loquercio, Elia Kaufmann, René Ranftl, Matthias Müller, Vladlen Koltun, and Davide Scaramuzza · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, et al · 2021
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Scaling up multi-task robotic reinforcement learning
Dmitry Kalashnikov, Jake Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, and Karol Hausman · 2022
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Learning robust perceptive locomotion for quadrupedal robots in the wild
Takahiro Miki, Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun, and Marco Hutter · 2022
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League: Guided skill learning and abstraction for long-horizon manipulation
Shuo Cheng and Danfei Xu · 2023
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Enhancing dexterity in robotic manipulation via hierarchical contact exploration
Xianyi Cheng, Sarvesh Patil, Zeynep Temel, Oliver Kroemer, and Matthew T Mason · 2023
Earlier work this paper cites.
Scaling up and distilling down: Language-guided robot skill acquisition
Huy Ha, Pete Florence, and Shuran Song · 2023
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Stable skill improvement of quadruped robot based on privileged information and curriculum guidance
Han Jiang, Teng Chen, Jingxuan Cao, Jian Bi, Guanglin Lu, Guoteng Zhang, Xuewen Rong, and Yibin Li · 2023
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Pre-and post-contact policy decomposition for non-prehensile manipulation with zero-shot sim-to-real transfer
Minchan Kim, Junhyek Han, Jaehyung Kim, and Beomjoon Kim · 2023
Cited alongside, same era.
Generative skill chaining: Long-horizon skill planning with diffusion models
Utkarsh Aashu Mishra, Shangjie Xue, Yongxin Chen, and Danfei Xu · 2023
Cited alongside, same era.
Dexpbt: Scaling up dexterous manipulation for hand-arm systems with population based training
Aleksei Petrenko, Arthur Allshire, Gavriel State, Ankur Handa, and Viktor Makoviychuk · 2023
Cited alongside, same era.
General in-hand object rotation with vision and touch
Haozhi Qi, Brent Yi, Sudharshan Suresh, Mike Lambeta, Yi Ma, Roberto Calandra, and Jitendra Malik · 2023
Cited alongside, same era.
Hybrid hierarchical learning for solving complex sequential tasks using the robotic manipulation network roman
Eleftherios Triantafyllidis, Fernando Acero, Zhaocheng Liu, and Zhibin Li · 2023
Cited alongside, same era.
Learning agile soccer skills for a bipedal robot with deep reinforcement learning
Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y Siegel, Roland Hafner, et al · 2024
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Practice makes perfect: Planning to learn skill parameter policies
Nishanth Kumar, Tom Silver, Willie McClinton, Linfeng Zhao, Stephen Proulx, Tomás Lozano-Pérez, Leslie Pack Kaelbling, and Jennifer Barry · 2024
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Multi-stage cable routing through hierarchical imitation learning
Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, and Sergey Levine · 2024
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Dexskills: Skill segmentation using haptic data for learning autonomous long-horizon robotic manipulation tasks
Xiaofeng Mao, Gabriele Giudici, Claudio Coppola, Kaspar Althoefer, Ildar Farkhatdinov, Zhibin Li, and Lorenzo Jamone · 2024
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Rapid locomotion via reinforcement learning
Gabriel B Margolis, Ge Yang, Kartik Paigwar, Tao Chen, and Pulkit Agrawal · 2024
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Mimicplay: Long-horizon imitation learning by watching human play
Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, and Anima Anandkumar · 2023
Cited alongside, same era.
Learning to grasp the ungraspable with emergent extrinsic dexterity
Wenxuan Zhou and David Held · 2023
Cited alongside, same era.
Ziwen Zhuang, Zipeng Fu, Jianren Wang, Christopher Atkeson, Soeren Schwertfeger, Chelsea Finn, and Hang Zhao · 2023
Cited alongside, same era.
Constrained skill discovery: Quadruped locomotion with unsupervised reinforcement learning
Vassil Atanassov, Wanming Yu, Alexander Luis Mitchell, Mark Nicholas Finean, and Ioannis Havoutis · 2024
Cited alongside, same era.
Demostart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots
Maria Bauza, Jose Enrique Chen, Valentin Dalibard, Nimrod Gileadi, Roland Hafner, Murilo F Martins, Joss Moore, Rugile Pevceviciute, Antoine Laurens, Dushyant Rao, et al · 2024
Cited alongside, same era.
Object-centric dexterous manipulation from human motion data
Yuanpei Chen, Chen Wang, Yaodong Yang, and C Karen Liu · 2024
Cited alongside, same era.
Acquiring musculoskeletal skills with curriculum-based reinforcement learning
Alberto Silvio Chiappa, Pablo Tano, Nisheet Patel, Abigaïl Ingster, Alexandre Pouget, and Alexander Mathis · 2024
Cited alongside, same era.
Sapg: Split and aggregate policy gradients
Jayesh Singla, Ananye Agarwal, and Deepak Pathak · 2024
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The art of imitation: Learning long-horizon manipulation tasks from few demonstrations
Jan Ole von Hartz, Tim Welschehold, Abhinav Valada, and Joschka Boedecker · 2024
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Multi-stage reinforcement learning for non-prehensile manipulation
Dexin Wang, Chunsheng Liu, Faliang Chang, Hengqiang Huan, and Kun Cheng · 2024
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Unidexfpm: Universal dexterous functional pre-grasp manipulation via diffusion policy
Tianhao Wu, Yunchong Gan, Mingdong Wu, Jingbo Cheng, Yaodong Yang, Yixin Zhu, and Hao Dong · 2024
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Anyrotate: Gravity-invariant in-hand object rotation with sim-to-real touch
Max Yang, Chenghua Lu, Alex Church, Yijiong Lin, Chris Ford, Haoran Li, Efi Psomopoulou, David AW Barton, and Nathan F Lepora · 2024
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Skill-aware mutual information optimisation for generalisation in reinforcement learning
Xuehui Yu, Mhairi Dunion, Xin Li, and Stefano V Albrecht · 2024
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SPIRE: Synergistic planning, imitation, and reinforcement learning for long-horizon manipulation
Zihan Zhou, Animesh Garg, Dieter Fox, Caelan Reed Garrett, and Ajay Mandlekar · 2024
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