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2-hour reinforcement learning simulation of a quadruped robot dog in MuJoCo

In a training platform built on a self-made MuJoCo physics simulator, the developer trained a quadruped robot dog simulation using reinforcement learning with motion imitation (style reference motions). Trained for only 2 hours on a MacBook Air CPU (no GPU), it learned a keyframe trot gait and balance. Joints are limited by a realistic hobby servo model in torque, speed curve, backlash, and latency, making the gait smoother than pure reinforcement learning. The simulation supports WASD-driven multidirectional control.

Part of the event: Robot Dog Learns Gait in 2-Hour CPU Training with MuJoCo Reinforcement Learning

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