Mjlab-RollerSprint2m-MicroDuck A perpetual policy for the microduck (61-D observation, 14 actions, 50 Hz, on rollers). Runs until told otherwise — a gait, loaded into a policy slot. The observation normalizer is baked into policy.onnx; feed raw observations. manifest.json follows schema 2 of the microduck policy manifest (docs/policy-manifest.md in the daemon repo). - taskid: Mjlab-RollerSprint2m-MicroDuck Same code, same uv.lock, same command, same seed. Training it again yields a comparable policy, not the same weights: GPU reinforcement learning is not bit-reproducible across machines.
Independent publisher
Stefen Pharai
stefo0
Physical AI
Models in Library1
Datasets in Library0
Models on Hugging Face2
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Published tasks: Robotics.
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