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Manipulation and locomotion are closely related problems that are often studied in isolation.
The evolution of social behavior
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Mujoco: A physics engine for model-based control
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Contact-invariant optimization for hand manipulation
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Quadrupedal locomotion using hierarchical operational space control
M. Hutter, H. Sommer, C. Gehring, M. Hoepflinger, M. Bloesch, and R. Siegwart · 2014
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Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics
A. Herzog, L. Righetti, F. Grimminger, P. Pastor, and S. Schaal · 2014
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Trust region policy optimization
J. Schulman, S. Levine, P. Abbeel, M. Jordan, and P. Moritz · 2015
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Cad2rl: Real single-image flight without a single real image
F. Sadeghi and S. Levine · 2016
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Online hierarchical optimization for humanoid control
S. Feng · 2016
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Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid
A. Herzog, N. Rotella, S. Mason, F. Grimminger, S. Schaal, and L. Righetti · 2016
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Combining model-based policy search with online model learning for control of physical humanoids
Sim-to-real reinforcement learning for deformable object manipulation
J. Matas, S. James, and A. J. Davison · 2018
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Data-efficient hierarchical reinforcement learning
O. Nachum, S. Gu, H. Lee, and S. Levine · 2018
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On the dualities between grasping and whole-body loco-manipulation tasks
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Crabot: A six-legged platform for environmental exploration and object manipulation
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Cooperative object transport in multi-robot systems: A review of the state-of-the-art
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I. Mordatch, N. Mishra, C. Eppner, and P. Abbeel · 2016
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Domain randomization for transferring deep neural networks from simulation to the real world
J. Tobin, R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel · 2017
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Towards Generalization and Simplicity in Continuous Control
A. Rajeswaran, K. Lowrey, E. Todorov, and S. Kakade · 2017
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Learning to walk via deep reinforcement learning
T. Haarnoja, A. Zhou, S. Ha, J. Tan, G. Tucker, and S. Levine · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 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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Learning dexterous in-hand manipulation
M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, et al · 2018
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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
A. Rajeswaran, V. Kumar, A. Gupta, G. Vezzani, J. Schulman, E. Todorov, and S. Levine · 2018
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B. Mehta, M. Diaz, F. Golemo, C. J. Pal, and L. Paull · 2019
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Bayessim: adaptive domain randomization via probabilistic inference for robotics simulators
F. Ramos, R. C. Possas, and D. Fox · 2019
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Near-optimal representation learning for hierarchical reinforcement learning
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Hierarchical reinforcement learning for quadruped locomotion
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End-to-end robotic reinforcement learning without reward engineering
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Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to-canonical adaptation networks
S. James, P. Wohlhart, M. Kalakrishnan, D. Kalashnikov, A. Irpan, J. Ibarz, S. Levine, R. Hadsell, and K. Bousmalis · 2019
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