Martin Peticco

Bridging the Sim-to-Real Gap for Athletic Loco-Manipulation

Training controllers via reinforcement learning (RL) in simulation has emerged as a powerful approach for synthesizing robust and agile robotic behaviors evaluated in reality. We push the envelope of the simulation training paradigm by exposing problems encountered when learning agile behaviors only…