The project implements a reinforcement learning pipeline for training humanoid robots to perform agile whole-body motor skills. It leverages NVIDIA’s physics simulation platforms (IsaacGym, IsaacSim, Genesis) and the HumanoidVerse framework to train motion-tracking skills with a delta action model. The core contribution is methods to align simulation physics with real-world dynamics to enable successful sim-to-real transfer of learned behaviors.