reinforcement-learning-robots

Use when training RL policies for robots (locomotion, manipulation, navigation), debugging reward hacking or sim-to-real transfer failures, choosing between scripted and learned control, or setting up Isaac Gym/Lab massively-parallel training. Provides PPO configuration, reward shaping patterns, dom