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We present a hierarchical framework that combines model-based control and reinforcement learning (RL) to synthesize robust controllers for a quadruped (the Unitree Laikago).
Gait and the energetics of locomotion in horses
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D. Precup · 2001
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Discovery of complex behaviors through contact-invariant optimization
I. Mordatch, E. Todorov, and Z. Popović · 2012
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A direct method for trajectory optimization of rigid bodies through contact
M. Posa, C. Cantu, and R. Tedrake · 2014
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Robots that can adapt like animals
A. Cully, J. Clune, D. Tarapore, and J.-B. Mouret · 2015
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Human-level control through deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al · 2015
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Z. Su, O. Kroemer, G. E. Loeb, G. S. Sukhatme, and S. Schaal · 2016
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Terrain-adaptive locomotion skills using deep reinforcement learning
X. B. Peng, G. Berseth, and M. van de Panne · 2016
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Deep reinforcement learning with double q-learning
H. Van Hasselt, A. Guez, and D. Silver · 2016
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Real-time motion planning of legged robots: A model predictive control approach
F. Farshidian, E. Jelavic, A. Satapathy, M. Giftthaler, and J. Buchli · 2017
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Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement learning
X. B. Peng, G. Berseth, K. Yin, and M. van de Panne · 2017
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Dynamic locomotion in the mit cheetah 3 through convex model-predictive control
J. Di Carlo, P. M. Wensing, B. Katz, G. Bledt, and S. Kim · 2018
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Gait and trajectory optimization for legged systems through phase-based end-effector parameterization
A. W. Winkler, D. C. Bellicoso, M. Hutter, and J. Buchli · 2018
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Sim-to-real: Learning agile locomotion for quadruped robots
J. Tan, T. Zhang, E. Coumans, A. Iscen, Y. Bai, D. Hafner, S. Bohez, and V. Vanhoucke · 2018
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Data-efficient hierarchical reinforcement learning
O. Nachum, S. S. Gu, H. Lee, and S. Levine · 2018
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Addressing function approximation error in actor-critic methods
S. Fujimoto, H. Van Hoof, and D. Meger · 2018
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Multi-agent manipulation via locomotion using hierarchical sim2real
O. Nachum, M. Ahn, H. Ponte, S. Gu, and V. Kumar · 2019
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Hierarchical reinforcement learning for quadruped locomotion
D. Jain, A. Iscen, and K. Caluwaerts · 2019
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Closing the sim-to-real loop: Adapting simulation randomization with real world experience
Y. Chebotar, A. Handa, V. Makoviychuk, M. Macklin, J. Issac, N. Ratliff, and D. Fox · 2019
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Learning agile robotic locomotion skills by imitating animals, 2020
X. B. Peng, E. Coumans, T. Zhang, T.-W. Lee, J. Tan, and S. Levine · 2020
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Variational contact-implicit trajectory optimization
Z. Manchester and S. Kuindersma · 2020
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Crocoddyl: An efficient and versatile framework for multi-contact optimal control
C. Mastalli, R. Budhiraja, W. Merkt, G. Saurel, B. Hammoud, M. Naveau, J. Carpentier, S. Vijayakumar, and N. Mansard · 2019
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Learning agile and dynamic motor skills for legged robots
J. Hwangbo, J. Lee, A. Dosovitskiy, D. Bellicoso, V. Tsounis, V. Koltun, and M. Hutter · 2019
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Online gait transitions and disturbance recovery for legged robots via the feasible impulse set
C. Boussema, M. J. Powell, G. Bledt, A. J. Ijspeert, P. M. Wensing, and S. Kim · 2019
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Learning locomotion skills for cassie: Iterative design and sim-to-real
Z. Xie, P. Clary, J. Dao, P. Morais, J. Hurst, and M. van de Panne · 2019
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Learning hierarchical control for robust in-hand manipulation
T. Li, K. Srinivasan, M. Q.-H. Meng, W. Yuan, and J. Bohg · 2019
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URL http://www.unitree.cc/e/action/ShowInfo.php?classid=6&id=1#
Laikago website
Cited in the paper.
Learning fast adaptation with meta strategy optimization
W. Yu, J. Tan, Y. Bai, E. Coumans, and S. Ha · 2020
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Deepgait: Planning and control of quadrupedal gaits using deep reinforcement learning
V. Tsounis, M. Alge, J. Lee, F. Farshidian, and M. Hutter · 2020
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Guided constrained policy optimization for dynamic quadrupedal robot locomotion
S. Gangapurwala, A. Mitchell, and I. Havoutis · 2020
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Isaac Gym - Preview Release , 2020
NVIDIA · 2020
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In-hand object pose tracking via contact feedback and gpu-accelerated robotic simulation
J. Liang, A. Handa, K. Van Wyk, V. Makoviychuk, O. Kroemer, and D. Fox · 2020
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