1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.RO2020★ 1 cited
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…
cs.RO2020
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…