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Controlling a non-statically stable biped is a difficult problem largely due to the complex hybrid dynamics involved.
Solving Rubik’s Cube with a Robot Hand
OpenAI, Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, and Lei Zhang · 1910
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Long Short-Term Memory
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State automata extraction from recurrent neural nets using k-means and fuzzy clustering
Adelmo Luis Cechin, D Regina, P Simon, and K Stertz · 2003
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Hybrid zero dynamics of planar biped walkers
Eric R Westervelt, Jessy W Grizzle, and Daniel E Koditschek · 2003
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Zero-Moment Point - Thirty Five Years of its Life
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Recurrent policy gradients
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Adam: A method for stochastic optimization
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Spring-Mass Walking With ATRIAS in 3D: Robust Gait Control Spanning Zero to 4.3 KPH on a Heavily Underactuated Bipedal Robot
Siavash Rezazadeh, Christian Hubicki, Mikhail Jones, Andrew Peekema, Johnathan Van Why, Andy Abate, and Jonathan Hurst · 2015
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Actuator control for the NASA-JSC valkyrie humanoid robot: A decoupled dynamics approach for torque control of series elastic robots
Nicholas Paine, Joshua S Mehling, James Holley, Nicolaus A Radford, Gwendolyn Johnson, Chien-Liang Fok, and Luis Sentis · 2015
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Memory-based control with recurrent neural networks
Nicolas Heess, Jonathan J. Hunt, Timothy P. Lillicrap, and David Silver · 2015
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Deep Recurrent Q-Learning for Partially Observable MDPs
Matthew Hausknecht and Peter Stone · 2015
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Explaining Recurrent Neural Network Predictions in Sentiment Analysis
Leila Arras, Grégoire Montavon, Klaus-Robert Müller, and Wojciech Samek · 2017
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Proximal Policy Optimization Algorithms , 2017
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Disturbance observer based linear feedback controller for compliant motion of humanoid robot
Mingon Kim, Jung Hoon Kim, Sanghyun Kim, Jaehoon Sim, and Jaeheung Park · 2018
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Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto · 2018
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Learning Locomotion Skills for Cassie: Iterative Design and Sim-to-Real
Zhaoming Xie, Patrick Clary, Jeremy Dao, Pedro Morais, Jonathan Hurst, and Michiel van de Panne · 2019
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Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, and Marco Hutter · 2019
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Learning Finite State Representations of Recurrent Policy Networks
Anurag Koul, Alan Fern, and Sam Greydanus · 2019
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Memory-Based Deep Reinforcement Learning for Obstacle Avoidance in UAV With Limited Environment Knowledge
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Preparing for the Unknown: Learning a Universal Policy with Online System Identification
Wenhao Yu, Jie Tan, C. Karen Liu, and Greg Turk · 2017
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Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
X. B. Peng, M. Andrychowicz, W. Zaremba, and P. Abbeel · 2018
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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
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A. Singla, S. Padakandla, and S. Bhatnagar · 2019
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Learning dexterous in-hand manipulation
OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Józefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, Jonas Schneider, Szymon Sidor, Josh Tobin, Peter Welinder, Lilian Weng, and Wojciech Zaremba · 2020
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