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This work explores the potential of using differentiable simulation for learning quadruped locomotion.
Legged robots that balance
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Pilco: A model-based and data-efficient approach to policy search
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On the difficulty of training recurrent neural networks
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Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
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Proximal policy optimization algorithms
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Learning agile and dynamic motor skills for legged robots
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A tour of reinforcement learning: The view from continuous control
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Mini cheetah: A platform for pushing the limits of dynamic quadruped control
B. Katz, J. D. Carlo, and S. Kim · 2019
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Real-time constrained nonlinear model predictive control on so (3) for dynamic legged locomotion
S. Hong, J.-H. Kim, and H.-W. Park · 2020
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Mastering atari, go, chess and shogi by planning with a learned model
J. Schrittwieser, I. Antonoglou, T. Hubert, K. Simonyan, L. Sifre, S. Schmitt, A. Guez, E. Lockhart, D. Hassabis, T. Graepel, et al · 2020
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Rma: Rapid motor adaptation for legged robots
A. Kumar, Z. Fu, D. Pathak, and J. Malik · 2021
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Brax–a differentiable physics engine for large scale rigid body simulation
C. D. Freeman, E. Frey, A. Raichuk, S. Girgin, I. Mordatch, and O. Bachem · 2021
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Plasticinelab: A soft-body manipulation benchmark with differentiable physics
Z. Huang, Y. Hu, T. Du, S. Zhou, H. Su, J. B. Tenenbaum, and C. Gan · 2021
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Efficient tactile simulation with differentiability for robotic manipulation
J. Xu, S. Kim, T. Chen, A. R. Garcia, P. Agrawal, W. Matusik, and S. Sueda · 2022
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Dojo: A differentiable physics engine for robotics
T. A. Howell, S. L. Cleac’h, J. Brüdigam, J. Z. Kolter, M. Schwager, and Z. Manchester · 2022
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Do differentiable simulators give better policy gradients?
H. J. Suh, M. Simchowitz, K. Zhang, and R. Tedrake · 2022
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Fast and efficient locomotion via learned gait transitions
Y. Yang, T. Zhang, E. Coumans, J. Tan, and B. Boots · 2022
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Deep whole-body control: learning a unified policy for manipulation and locomotion
Z. Fu, X. Cheng, and D. Pathak · 2023
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Robot parkour learning
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Gradients are not all you need
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Fast and feature-complete differentiable physics for articulated rigid bodies with contact
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Rapid locomotion via reinforcement learning
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Diffmimic: Efficient motion mimicking with differentiable physics
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Mastering diverse domains through world models
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Daydreamer: World models for physical robot learning
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Reaching the limit in autonomous racing: Optimal control versus reinforcement learning
Y. Song, A. Romero, M. Müller, V. Koltun, and D. Scaramuzza · 2023
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Cajun: Continuous adaptive jumping using a learned centroidal controller
Y. Yang, G. Shi, X. Meng, W. Yu, T. Zhang, J. Tan, and B. Boots · 2023
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Extreme parkour with legged robots
X. Cheng, K. Shi, A. Agarwal, and D. Pathak · 2024
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