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Dexterous manipulation remains an open problem in robotics.
Robot competitions-ideal benchmarks for robotics research
Sven Behnke · 2006
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Causalworld: A robotic manipulation benchmark for causal structure and transfer learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Yoshua Bengio, Bernhard Schölkopf, Manuel Wüthrich, and Stefan Bauer · 2010
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Competitions for Benchmarking: Task and Functionality Scoring Complete Performance Assessment
F Amigoni, E Bastianelli, J Berghofer, A Bonarini, G Fontana, N Hochgeschwender, L Iocchi, G Kraetzschmar, P Lima, M Matteucci, P Miraldo, D Nardi, and V Schiaffonati · 2015
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Toward Replicable and Measurable Robotics Research [From the Guest Editors]
F Bonsignorio and A P del Pobil · 2015
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Pybullet, a python module for physics simulation for games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2016
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Benchmarking deep reinforcement learning for continuous control
Yan Duan, Xi Chen, Rein Houthooft, John Schulman, and Pieter Abbeel · 2016
Earlier work this paper cites.
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Extending the openai gym for robotics: a toolkit for reinforcement learning using ros and gazebo
Iker Zamora, Nestor Gonzalez Lopez, Victor Mayoral Vilches, and Alejandro Hernandez Cordero · 2016
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Emergence of Locomotion Behaviours in Rich Environments
Nicolas Heess, T B Dhruva, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S M Ali Eslami, Martin Riedmiller, and David Silver · 2017
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Duckietown: An open, inexpensive and flexible platform for autonomy education and research
Liam Paull, Jacopo Tani, Heejin Ahn, Javier Alonso-Mora, Luca Carlone, Michal Cap, Yu Fan Chen, Changhyun Choi, Jeff Dusek, Yajun Fang, Daniel Hoehener, Shih-Yuan Liu, Michael Novitzky, Igor Franzoni Okuyama, Jason Pazis, Guy Rosman, Valerio Varricchio, Hsueh-Cheng Wang, Dmitry Yershov, Hang Zhao, Michael Benjamin, Christopher Carr, Maria Zuber, Sertac Karaman, Emilio Frazzoli, Domitilla Del Vecchio, Daniela Rus, Jonathan How, John Leonard, and Andrea Censi · 2017
Cited alongside, same era.
The robotarium: A remotely accessible swarm robotics research testbed
Daniel Pickem, Paul Glotfelter, Li Wang, Mark Mote, Aaron Ames, Eric Feron, and Magnus Egerstedt · 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.
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto, Herke van Hoof, and David Meger · 2018
Cited alongside, same era.
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Real robot challenge phase 2: Manipulating objects using high-level coordination of motion primitives
Anonymous · 2020
Later among the works it cites.
An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research
Felix Grimminger, Avadesh Meduri, Majid Khadiv, Julian Viereck, Manuel Wüthrich, Maximilien Naveau, Vincent Berenz, Steve Heim, Felix Widmaier, Jonathan Fiene, Alexander Badri-Spröwitz, and Ludovic Righetti · 2020
Later among the works it cites.
TriFinger: An Open-Source Robot for Learning Dexterity
Manuel Wüthrich, Felix Widmaier, Felix Grimminger, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, and Stefan Bauer · 2020
Later among the works it cites.
Transferring dexterous manipulation from gpu simulation to a remote real-world trifinger
Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, and Animesh Garg · 2021
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Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
Cited alongside, same era.
Deep reinforcement learning that matters
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, and David Meger · 2018
Cited alongside, same era.
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al · 2018
Cited alongside, same era.
Robel: Robotics benchmarks for learning with low-cost robots
Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, and Vikash Kumar · 2019
Cited alongside, same era.
PyRobot: An Open-source Robotics Framework for Research and Benchmarking
Adithyavairavan Murali, Tao Chen, Kalyan Vasudev Alwala, Dhiraj Gandhi, Lerrel Pinto, Saurabh Gupta, and Abhinav Gupta · 2019
Cited alongside, same era.
Replab: A reproducible low-cost arm benchmark platform for robotic learning
Brian Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, and Dinesh Jayaraman · 2019
Cited alongside, same era.
Benchmarking in Manipulation Research: Using the Yale-CMU-Berkeley Object and Model Set
B Calli, A Walsman, A Singh, S Srinivasa, P Abbeel, and A M Dollar
Cited in the paper.
Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols
Berk Calli, Aaron Walsman, Arjun Singh, Siddhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar
Cited in the paper.
Anonymous · 2021
Closest in time.
Dexterous manipulation primitives for the real robot challenge, 2021
Claire Chen, Krishnan Srinivasan, Jeffrey Zhang, Junwu Zhang, Lin Shao, Shenli Yuan, Preston Culbertson, Hongkai Dai, Mac Schwager, and Jeannette Bohg · 2021
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Benchmarking structured policies and policy optimization for real-world dexterous object manipulation, 2021
Niklas Funk, Charles Schaff, Rishabh Madan, Takuma Yoneda, Julen Urain De Jesus, Joe Watson, Ethan K. Gordon, Felix Widmaier, Stefan Bauer, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Matthew R. Walter, and Jan Peters · 2021
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Solving the real robot challenge using deep reinforcement learning, 2021
Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel O’Connor, and Stephen J. Redmond · 2021
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Real-world dexterous object manipulation based deep reinforcement learning, 2021
Qingfeng Yao, Jilong Wang, and Shuyu Yang · 2021
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Grasp and motion planning for dexterous manipulation for the real robot challenge, 2021
Takuma Yoneda, Charles Schaff, Takahiro Maeda, and Matthew Walter · 2021
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