Training our own reinforcement-learning locomotion policies for the M20.
This page is a stub.
Getting started
DEEP Robotics’ rl_training repository trains policies in Isaac Lab, and their RL training and deployment tutorial walks through the workflow. A trained policy outputs joint angles and wheel speeds; see Control Interface for what it sends to the robot.