roller-sprint-2m-reference
Pollen's reference for the Microduck Arena's 2 m Roller Sprint: the roller_sprint_2m challenge of microduck-challenges trained unchanged with its recipe (4096 envs, 3000 iterations, seed 1).
A perpetual policy for the microduck (61-D observation, 14 actions, 50 Hz, on rollers). Runs until told otherwise — a gait for the walk slot.
Run it on a robot
sudo robotctl policy load walk pollen-robotics/microduck-roller-sprint-2m-reference
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).
Training
- task_id:
Mjlab-RollerSprint2m-MicroDuck - repo:
https://github.com/pollen-robotics/microduck-challenges.git - branch:
main - commit:
611b6453c - checkpoint:
2999 - seed:
1 - base:
mjlab-microduck 0.1.0 @ 981a279c6 - started:
2026-09-26T04:21:50Z
Reproduce
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.
git clone https://github.com/pollen-robotics/microduck-challenges.git
cd microduck-challenges
git checkout 611b6453c
uv sync
uv run train Mjlab-RollerSprint2m-MicroDuck --env.scene.num-envs 4096 --agent.max-iterations 3000 --agent.seed 1 --agent.logger tensorboard --agent.run-name reference
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