Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner
Philémon Brakel,Steven Bohez,Leonard Hasenclever,Nicolas Heess,Konstantinos Bousmalis,Philémon Brakel,Steven Bohez,Leonard Hasenclever,Nicolas Heess,Konstantinos Bousmalis
We propose a simple imitation learning procedure for learning locomotion controllers that can walk over very challenging terrains. We use trajectory optimization (TO) to produce a large dataset of trajectories over procedurally generated terrains and use Reinforcement Learning (RL) to imitate these trajectories. We demonstrate with a realistic model of the ANYmal robot that the learned controllers...
