This repository implements a reinforcement learning starter kit for the Unitree Go1 robot, enabling sim-to-real transfer of locomotion policies. It builds on the legged gym environment to train robot controllers that can generalize across different behavioral modes. The toolkit includes simulation training pipelines, real-world deployment utilities, and tools for analyzing policy performance on physical hardware.