198 citations · 248 across the 6 of their papers we have counts for
10 papers
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors
Steven Bohez, Saran Tunyasuvunakool, Philemon Brakel +18
We investigate the use of prior knowledge of human and animal movement to learn reusable locomotion skills for real legged robots. Our approach builds upon previous work on imitati…
Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner
Philemon Brakel, Steven Bohez, Leonard Hasenclever +2
Dynamic quadruped locomotion over challenging terrains with precise foot placements is a hard problem for both optimal control methods and Reinforcement Learning (RL). Non-linear s…
dm_control: Software and Tasks for Continuous Control
Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal +8
The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A MuJoCo wrapper provides c…
Value constrained model-free continuous control
Steven Bohez, Abbas Abdolmaleki, Michael Neunert +3
The naive application of Reinforcement Learning algorithms to continuous control problems -- such as locomotion and manipulation -- often results in policies which rely on high-amp…
Relative Entropy Regularized Policy Iteration
Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave +5
We present an off-policy actor-critic algorithm for Reinforcement Learning (RL) that combines ideas from gradient-free optimization via stochastic search with learned action-value…
Sim-to-Real: Learning Agile Locomotion For Quadruped Robots
Jie Tan, Tingnan Zhang, Erwin Coumans +5
Designing agile locomotion for quadruped robots often requires extensive expertise and tedious manual tuning. In this paper, we present a system to automate this process by leverag…