Event
Robot Dog Learns Gait in 2-Hour CPU Training with MuJoCo Reinforcement Learning
1 reports · 1 sources
Reddit user /u/Safe_Tone1529 reports that on a training platform they built on top of the MuJoCo physics simulator, they used reinforcement learning with motion imitation (referencing keyframe motions) to train a quadruped robot dog simulation, training for only 2 hours on a MacBook Air's CPU (no GPU), and the robot dog learned to imitate the keyframe trot gait, maintain balance, and support WASD multi-directional control. The developer states that the joints are limited by torque, speed curves, backlash, and latency according to a realistic hobby servo model, rather than motors with unlimited output; compared with pure reinforcement learning, adding motion imitation makes the gait smoother. The above is all the developer's own account, and the report provides no third-party verification.
Report timeline
- 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.
Reddit r/robotics ·