Reactive Stepping for Humanoid Robots using Reinforcement Learning: Application to Standing Push Recovery on the Exoskeleton Atalante

Alexis Duburcq,Fabian Schramm,Guilhem Boéris,Nicolas Bredeche,Yann Chevaleyre,Alexis Duburcq,Fabian Schramm,Guilhem Boéris,Nicolas Bredeche,Yann Chevaleyre

State-of-the-art reinforcement learning is now able to learn versatile locomotion, balancing and push-recovery capabilities for bipedal robots in simulation. Yet, the reality gap has mostly been overlooked and the simulated results hardly transfer to real hardware. Either it is unsuccessful in practice because the physics is over-simplified and hardware limitations are ignored, or regularity is no...