The framework provides a complete workflow for training RL policies to control humanoid robot locomotion (walking and running). It leverages IsaacLab for physics simulation, RSL_RL for reinforcement learning, and supports sim-to-sim transfer between IsaacSim and MuJoCo. The system includes sensor integration and AMP (Adversarial Motion Priors) animation support for natural motion generation.