Fetching the paper…
Reading the bibliography…
We introduce MuJoCo Playground, a fully open-source framework for robot learning built with MJX, with the express goal of streamlining simulation, training, and sim-to-real transfer onto robots.
Design and use paradigms for gazebo, an open-source multi-robot simulator
Nathan Koenig and Andrew Howard · 2004
Earlier work this paper cites.
Reinforcement learning with augmented data
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, and Aravind Srinivas · 2004
Earlier work this paper cites.
What matters in on-policy reinforcement learning? a large-scale empirical study
Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk, Manu Orsini, Sertan Girgin, Raphael Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, et al · 2006
Earlier work this paper cites.
Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
Earlier work this paper cites.
Reinforcement learning in robotics: A survey
Jens Kober, J Andrew Bagnell, and Jan Peters · 2013
Earlier work this paper cites.
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, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
Earlier work this paper cites.
ar_track_alvar, 2016
Scott Niekum and Isaac I.Y. Saito · 2016
Earlier work this paper cites.
Experimental evaluation of simple estimators for humanoid robots
T. Flayols, A. Del Prete, P. Wensing, A. Mifsud, M. Benallegue, and O. Stasse · 2017
Earlier work this paper cites.
Searching for activation functions, 2017
Prajit Ramachandran, Barret Zoph, and Quoc V. Le · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Domain randomization for transferring deep neural networks from simulation to the real world
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
Earlier work this paper cites.
JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 2018
Earlier work this paper cites.
Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
Earlier work this paper cites.
Gpu-accelerated robotic simulation for distributed reinforcement learning
Jacky Liang, Viktor Makoviychuk, Ankur Handa, Nuttapong Chentanez, Miles Macklin, and Dieter Fox · 2018
Earlier work this paper cites.
Asymmetric actor critic for image-based robot learning
Lerrel Pinto, Marcin Andrychowicz, Peter Welinder, Wojciech Zaremba, and Pieter Abbeel · 2018
Earlier work this paper cites.
Sim-to-real: Learning agile locomotion for quadruped robots
Jie Tan, Tingnan Zhang, Erwin Coumans, Atil Iscen, Yunfei Bai, Danijar Hafner, Steven Bohez, and Vincent Vanhoucke · 2018
Earlier work this paper cites.
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
Earlier work this paper cites.
Closing the sim-to-real loop: Adapting simulation randomization with real world experience
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk, Miles Macklin, Jan Issac, Nathan Ratliff, and Dieter Fox · 2019
Earlier work this paper cites.
Difftaichi: Differentiable programming for physical simulation
Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, and Frédo Durand · 2019
Earlier work this paper cites.
Robust recovery controller for a quadrupedal robot using deep reinforcement learning
Joonho Lee, Jemin Hwangbo, and Marco Hutter · 2019
Earlier work this paper cites.
Benchmarking the performance and energy efficiency of ai accelerators for ai training
Yuxin Wang, Qiang Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Kaiyong Zhao, and Xiaowen Chu · 2020
Earlier work this paper cites.
Sim-to-real transfer in deep reinforcement learning for robotics: a survey
Wenshuai Zhao, Jorge Peña Queralta, and Tomi Westerlund · 2020
Earlier work this paper cites.
Onnx runtime
ONNX Runtime developers · 2021
Cited alongside, same era.
Brax-a differentiable physics engine for large scale rigid body simulation, 2021
C Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, and Olivier Bachem · 2021
Cited alongside, same era.
Analytical inverse kinematics for franka emika panda – a geometrical solver for 7-dof manipulators with unconventional design
Yanhao He and Steven Liu · 2021
Cited alongside, same era.
How to train your robot with deep reinforcement learning: lessons we have learned
Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, and Sergey Levine · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Leap hand: Low-cost, efficient, and anthropomorphic hand for robot learning
Kenneth Shaw, Ananye Agarwal, and Deepak Pathak · 2023
Later among the works it cites.
Ziwen Zhuang, Zipeng Fu, Jianren Wang, Christopher Atkeson, Soeren Schwertfeger, Chelsea Finn, and Hang Zhao · 2023
Later among the works it cites.
Aloha 2: An enhanced low-cost hardware for bimanual teleoperation
Jorge ALOHA 2 Team, Aldaco, Travis Armstrong, Robert Baruch, Jeff Bingham, Sanky Chan, Kenneth Draper, Debidatta Dwibedi, Chelsea Finn, Pete Florence, Spencer Goodrich, et al · 2024
Later among the works it cites.
Extreme parkour with legged robots
Xuxin Cheng, Kexin Shi, Ananye Agarwal, and Deepak Pathak · 2024
Later among the works it cites.
Corn: Contact-based object representation for nonprehensile manipulation of general unseen objects
Yoonyoung Cho, Junhyek Han, Yoontae Cho, and Beomjoon Kim · 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Learning free gait transition for quadruped robots via phase-guided controller
Yecheng Shao, Yongbin Jin, Xianwei Liu, Weiyan He, Hongtao Wang, and Wei Yang · 2021
Cited alongside, same era.
Mastering visual continuous control: Improved data-augmented reinforcement learning
Denis Yarats, Rob Fergus, Alessandro Lazaric, and Lerrel Pinto · 2021
Cited alongside, same era.
A system for general in-hand object re-orientation
Tao Chen, Jie Xu, and Pulkit Agrawal · 2022
Cited alongside, same era.
Concurrent training of a control policy and a state estimator for dynamic and robust legged locomotion
Gwanghyeon Ji, Juhyeok Mun, Hyeongjun Kim, and Jemin Hwangbo · 2022
Cited alongside, same era.
Warp: A high-performance python framework for gpu simulation and graphics
Miles Macklin · 2022
Cited alongside, same era.
Learning robust perceptive locomotion for quadrupedal robots in the wild
Takahiro Miki, Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun, and Marco Hutter · 2022
Cited alongside, same era.
Learning to walk in minutes using massively parallel deep reinforcement learning
Nikita Rudin, David Hoeller, Philipp Reist, and Marco Hutter · 2022
Cited alongside, same era.
Later among the works it cites.
Genesis: A universal and generative physics engine for robotics and beyond, December 2024
Genesis-Authors · 2024
Later among the works it cites.
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
Later among the works it cites.
Sim2real rope cutting with a surgical robot using vision-based reinforcement learning
Mustafa Haiderbhai, Radian Gondokaryono, Andrew Wu, and Lueder A. Kahrs · 2024
Later among the works it cites.
Td-mpc2: Scalable, robust world models for continuous control, 2024
Nicklas Hansen, Hao Su, and Xiaolong Wang · 2024
Later among the works it cites.
Evolving control: Evolved high frequency control for continuous control tasks
Samuel Holt, Todor Davchev, Dhruva Tirumala, Ben Moran, Yixin Lin, Antoine Laurens, Atil Iscen, Erik Frey, Markus Wulfmeier, Francesco Romano, and Nicolas Heess · 2024
Later among the works it cites.
Berkeley humanoid: A research platform for learning-based control
Qiayuan Liao, Bike Zhang, Xuanyu Huang, Xiaoyu Huang, Zhongyu Li, and Koushil Sreenath · 2024
Later among the works it cites.
Learning humanoid locomotion with perceptive internal model
Junfeng Long, Junli Ren, Moji Shi, Zirui Wang, Tao Huang, Ping Luo, and Jiangmiao Pang · 2024
Later among the works it cites.
MuJoCo XLA (MJX)
MuJoCo XLA Authors · 2024
Later among the works it cites.
Learning humanoid locomotion over challenging terrain
Ilija Radosavovic, Sarthak Kamat, Trevor Darrell, and Jitendra Malik · 2024
Later among the works it cites.
High-throughput batch rendering for embodied ai
Luc Guy Rosenzweig, Brennan Shacklett, Warren Xia, and Kayvon Fatahalian · 2024
Later among the works it cites.
Humanoidbench: Simulated humanoid benchmark for whole-body locomotion and manipulation
Carmelo Sferrazza, Dun-Ming Huang, Xingyu Lin, Youngwoon Lee, and Pieter Abbeel · 2024
Later among the works it cites.
Dextrah-rgb: Visuomotor policies to grasp anything with dexterous hands
Ritvik Singh, Arthur Allshire, Ankur Handa, Nathan Ratliff, and Karl Van Wyk · 2024
Later among the works it cites.
Maniskill3: Gpu parallelized robotics simulation and rendering for generalizable embodied ai
Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichsen, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse-kai Chan, et al · 2024
Later among the works it cites.
Efficientzero v2: Mastering discrete and continuous control with limited data
Shengjie Wang, Shaohuai Liu, Weirui Ye, Jiacheng You, and Yang Gao · 2024
Later among the works it cites.
Full-order sampling-based mpc for torque-level locomotion control via diffusion-style annealing
Haoru Xue, Chaoyi Pan, Zeji Yi, Guannan Qu, and Guanya Shi · 2024
Later among the works it cites.
rsl_rl: Fast and simple implementation of rl algorithms, designed to run fully on gpu
leggedrobotics · 2025
Closest in time.