63 citations · 124 across the 14 of their papers we have counts for
5 papers · 1 filter
Learning Task Space Actions for Bipedal Locomotion
Helei Duan, Jeremy Dao, Kevin Green +3
Recent work has demonstrated the success of reinforcement learning (RL) for training bipedal locomotion policies for real robots. This prior work, however, has focused on learning…
Sim-to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition
Jonah Siekmann, Yesh Godse, Alan Fern +1
We study the problem of realizing the full spectrum of bipedal locomotion on a real robot with sim-to-real reinforcement learning (RL). A key challenge of learning legged locomotio…
Learning Spring Mass Locomotion: Guiding Policies with a Reduced-Order Model
Kevin Green, Yesh Godse, Jeremy Dao +3
In this paper, we describe an approach to achieve dynamic legged locomotion on physical robots which combines existing methods for control with reinforcement learning. Specifically…
Learning Memory-Based Control for Human-Scale Bipedal Locomotion
Jonah Siekmann, Srikar Valluri, Jeremy Dao +4
Controlling a non-statically stable biped is a difficult problem largely due to the complex hybrid dynamics involved. Recent work has demonstrated the effectiveness of reinforcemen…
Planning for the Unexpected: Explicitly Optimizing Motions for Ground Uncertainty in Running
Kevin Green, Ross L. Hatton, Jonathan Hurst
We propose a method to generate actuation plans for a reduced order, dynamic model of bipedal running. This method explicitly enforces robustness to ground uncertainty. The plan ge…