Microduck RL

An open-source set of reinforcement-learning training environments for Pollen Robotics' Microduck bipedal robot, built on mjlab with MuJoCo Warp and PPO. It trains walking, standing, recovery, sitting, ground-picking, kicking, rolling, and roller-skating policies, with flat, rough, slope, and backlash variants where applicable. The environments encode a sim-to-real pipeline using BAM actuator physics for Dynamixel XL330 servos, domain randomization for battery voltage, voltage sag, command delay, and friction, and simulated gear backlash with output-side encoder feedback. Policies use a shared 61-dimensional observation contract for runtime hot-swapping, are trained at 50 Hz, exported to ONNX with the observation normalizer embedded, and deployed by the Microduck runtime. Training runs locally through a CUDA GPU or can be submitted to Hugging Face Jobs; the project is licensed under Apache 2.0, while its 3D model files use CC BY-SA-NC.