hill-climb-1m5-reference
Pollen's reference for the Microduck Arena's 1.5 m Hill Climb: the hill_climb_1m5 challenge of microduck-challenges trained unchanged with its recipe (4096 envs, 3000 iterations, seed 1); checkpoint 1000, its fastest on the Arena.
A perpetual policy for the microduck (61-D observation, 14 actions, 50 Hz). Runs until told otherwise — a gait for the walk slot.
Run it on a robot
sudo robotctl policy load walk pollen-robotics/microduck-hill-climb-1m5-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-HillClimb1m5-MicroDuck - repo:
https://github.com/pollen-robotics/microduck-challenges.git - branch:
heading-hold - commit:
7a668f11c - checkpoint:
1000 - seed:
1 - base:
mjlab-microduck 0.1.0 @ 981a279c6 - started:
2026-09-28T15:02:36Z
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 7a668f11c
uv sync
uv run train Mjlab-HillClimb1m5-MicroDuck --env.scene.num-envs 4096 --agent.max-iterations 3000 --agent.seed 1 --agent.logger tensorboard --agent.run-name reference
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