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Humanoid robots hold great promise in assisting humans in diverse environments and tasks, due to their flexibility and adaptability leveraging human-like morphology.
Hierarchical learning of robot skills by reinforcement
L-J Lin · 1993
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Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning
Richard S Sutton, Doina Precup, and Satinder Singh · 1999
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Humanoid multimodal tactile-sensing modules
Philipp Mittendorfer and Gordon Cheng · 2011
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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The arcade learning environment: An evaluation platform for general agents
M. G. Bellemare, Y. Naddaf, J. Veness, and M. Bowling · 2013
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Optimization based full body control for the atlas robot
Siyuan Feng, Eric Whitman, X Xinjilefu, and Christopher G Atkeson · 2014
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
Scott Kuindersma, Robin Deits, Maurice Fallon, Andrés Valenzuela, Hongkai Dai, Frank Permenter, Twan Koolen, Pat Marion, and Russ Tedrake · 2016
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The option-critic architecture
Pierre-Luc Bacon, Jean Harb, and Doina Precup · 2017
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One-shot imitation learning
Yan Duan, Marcin Andrychowicz, Bradly Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, and Wojciech Zaremba · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Data-efficient hierarchical reinforcement learning
Ofir Nachum, Shixiang Shane Gu, Honglak Lee, and Sergey Levine · 2018
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Multi-goal reinforcement learning: Challenging robotics environments and request for research
Matthias Plappert, Marcin Andrychowicz, Alex Ray, Bob McGrew, Bowen Baker, Glenn Powell, Jonas Schneider, Josh Tobin, Maciek Chociej, Peter Welinder, Vikash Kumar, and Wojciech Zaremba · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy P. Lillicrap, and Martin A. Riedmiller · 2018
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Solving rubik’s cube with a robot hand
Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, et al · 2019
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Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning
Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, and Karol Hausman · 2019
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Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, and Marco Hutter · 2019
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Stable baselines3, 2019
Antonin Raffin, Ashley Hill, Maximilian Ernestus, Adam Gleave, Anssi Kanervisto, and Noah Dormann · 2019
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Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, and Sergey Levine · 2019
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Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J. Davison · 2020
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Learning to coordinate manipulation skills via skill behavior diversification
Youngwoon Lee, Jingyun Yang, and Joseph J. Lim · 2020
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Softgym: Benchmarking deep reinforcement learning for deformable object manipulation
Xingyu Lin, Yufei Wang, Jake Olkin, and David Held · 2020
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Catch & carry: reusable neural controllers for vision-guided whole-body tasks
Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, and Nicolas Heess · 2020
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Learning dexterous in-hand manipulation
OpenAI, Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, 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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Accelerating reinforcement learning with learned skill priors
Karl Pertsch, Youngwoon Lee, and Joseph J. Lim · 2020
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dm_control: Software and tasks for continuous control
Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, and Nicolas Heess · 2020
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robosuite: A modular simulation framework and benchmark for robot learning
Locomujoco: A comprehensive imitation learning benchmark for locomotion
Firas Al-Hafez, Guoping Zhao, Jan Peters, and Davide Tateo · 2023
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SAR: Generalization of Physiological Dexterity via Synergistic Action Representation
Cameron H Berg, Vittorio Caggiano, and Vikash Kumar · 2023
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Myodex: a generalizable prior for dexterous manipulation
Vittorio Caggiano, Sudeep Dasari, and Vikash Kumar · 2023
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Bi-dexhands: Towards human-level bimanual dexterous manipulation
Yuanpei Chen, Yiran Geng, Fangwei Zhong, Jiaming Ji, Jiechuang Jiang, Zongqing Lu, Hao Dong, and Yaodong Yang · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, and Shuran Song · 2023
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dibyaghosh/jaxrl_m, 2023
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Yuke Zhu, Josiah Wong, Ajay Mandlekar, and Roberto Martín-Martín · 2020
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Robodesk: A multi-task reinforcement learning benchmark
Harini Kannan, Danijar Hafner, Chelsea Finn, and Dumitru Erhan · 2021
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Rma: Rapid motor adaptation for legged robots
Ashish Kumar, Zipeng Fu, Deepak Pathak, and Jitendra Malik · 2021
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IKEA furniture assembly environment for long-horizon complex manipulation tasks
Youngwoon Lee, Edward S Hu, and Joseph J Lim · 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, and Gavriel State · 2021
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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Amp: Adversarial motion priors for stylized physics-based character control
Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, and Angjoo Kanazawa · 2021
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Behavior: Benchmark for everyday household activities in virtual, interactive, and ecological environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach, Roberto Martín-Martín, Fei Xia, Kent Elliott Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, Karen Liu, Silvio Savarese, Hyowon Gweon, Jiajun Wu, and Li Fei-Fei · 2021
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Dibya Ghosh · 2023
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Learning agile soccer skills for a bipedal robot with deep reinforcement learning
Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, and Nicolas Heess · 2023
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Mastering diverse domains through world models
Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, and Timothy Lillicrap · 2023
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Furniturebench: Reproducible real-world benchmark for long-horizon complex manipulation
Minho Heo, Youngwoon Lee, Doohyun Lee, and Joseph J. Lim · 2023
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Learning humanoid locomotion with transformers
Ilija Radosavovic, Tete Xiao, Bike Zhang, Trevor Darrell, Jitendra Malik, and Koushil Sreenath · 2023
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Carmelo Sferrazza, Younggyo Seo, Hao Liu, Youngwoon Lee, and Pieter Abbeel · 2023
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Physhoi: Physics-based imitation of dynamic human-object interaction
Yinhuai Wang, Jing Lin, Ailing Zeng, Zhengyi Luo, Jian Zhang, and Lei Zhang · 2023
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Hierarchical planning and control for box loco-manipulation
Zhaoming Xie, Jonathan Tseng, Sebastian Starke, Michiel van de Panne, and C Karen Liu · 2023
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Robot synesthesia: In-hand manipulation with visuotactile sensing
Ying Yuan, Haichuan Che, Yuzhe Qin, Binghao Huang, Zhao-Heng Yin, Kang-Won Lee, Yi Wu, Soo-Chul Lim, and Xiaolong Wang · 2023
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Robopianist: Dexterous piano playing with deep reinforcement learning
Kevin Zakka, Philipp Wu, Laura Smith, Nimrod Gileadi, Taylor Howell, Xue Bin Peng, Sumeet Singh, Yuval Tassa, Pete Florence, Andy Zeng, and Pieter Abbeel · 2023
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Learning physically simulated tennis skills from broadcast videos
Haotian Zhang, Ye Yuan, Viktor Makoviychuk, Yunrong Guo, Sanja Fidler, Xue Bin Peng, and Kayvon Fatahalian · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
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Robot parkour learning
Ziwen Zhuang, Zipeng Fu, Jianren Wang, Christopher G Atkeson, Sören Schwertfeger, Chelsea Finn, and Hang Zhao · 2023
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Expressive whole-body control for humanoid robots
Xuxin Cheng, Yandong Ji, Junming Chen, Ruihan Yang, Ge Yang, and Xiaolong Wang · 2024
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Mobile aloha: Learning bimanual mobile manipulation with low-cost whole-body teleoperation
Zipeng Fu, Tony Z Zhao, and Chelsea Finn · 2024
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Td-mpc2: Scalable, robust world models for continuous control
Nicklas Hansen, Hao Su, and Xiaolong Wang · 2024
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Mimo: A multi-modal infant model for studying cognitive development
Dominik Mattern, Pierre Schumacher, Francisco M López, Marcel C Raabe, Markus R Ernst, Arthur Aubret, and Jochen Triesch · 2024
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