907 citations · 1.3k across the 17 of their papers we have counts for
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Dynamics Randomization Revisited:A Case Study for Quadrupedal Locomotion
Zhaoming Xie, Xingye Da, Michiel van de Panne +2
Understanding the gap between simulation and reality is critical for reinforcement learning with legged robots, which are largely trained in simulation. However, recent work has re…
Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning
Daniele Reda, Tianxin Tao, Michiel van de Panne
Learning to locomote is one of the most common tasks in physics-based animation and deep reinforcement learning (RL). A learned policy is the product of the problem to be solved, a…
ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills
Zhaoming Xie, Hung Yu Ling, Nam Hee Kim +1
Humans are highly adept at walking in environments with foot placement constraints, including stepping-stone scenarios where the footstep locations are fully constrained. Finding g…