microduck-walk-seed42

arabellako22/microduck-walk-seed42

microduck-walk-seed42 is a robotics model from arabellako22. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for microduck. The card lists the license as apache-2.0.

This repository documents a personal study run that installs Pollen Robotics' Microduck simulator, trains a flat-ground walking policy with PPO, exports the normalized policy to ONNX, and validates the release artifac…

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At a glance

Task: Robotics
Library: microduck
License: apache-2.0
Access: Public
Created: Sep 7, 2026
Updated: Sep 29, 2026
SHA: 8b82dd14

Model card

From the Hugging Face model README

Microduck flat-walking PPO — Colab study run

Training setup

Task: Mjlab-Velocity-Flat-MicroDuck
Algorithm: PPO via rsl_rl
Simulator: mjlab / MuJoCo Warp
Parallel environments: 4096
Training iterations: 4000
Seed: 42
Source revision: 29e887ecfbf5
Export: official scripts/export.py; observation normalizer baked into ONNX

Validation

ONNX contract: [1, 61] -> [1, 14]
Publisher smoke test: finite and non-constant output
Simulation video: 8.00 seconds, rendered with egl
Commanded forward velocity: 0.50 m/s
Measured mean forward velocity: 0.247 m/s
Terminations during rollout: 0
Policy SHA-256: 82a2369fe642eda505ee6d60c7ed26aafd177eb7484030834cd04e5a53035213
Video SHA-256: c73cb27596c2a7c87282e7bcb0583647cc44539928d18e74f8ce8bfbc04704ee

The video was reviewed before publication as a qualitative success check. This run has not been tested on a physical Microduck. One video and one seed are not a statistical performance benchmark.

Multi-seed headless evaluation

The uploaded policy.onnx was evaluated without rendering across 10 deterministic evaluation seeds. This tests one policy trained with seed 42; it is not a multiple-training-seed study.

Eval seed	Mean reward/step	Mean velocity (m/s)	Mean absolute velocity error (m/s)	Success
100	0.1413	0.236	0.264	✅
101	0.1487	0.271	0.232	✅
102	0.1460	0.225	0.276	✅
103	0.1482	0.291	0.212	✅
104	0.1444	0.227	0.274	✅
105	0.1447	0.221	0.279	✅
106	0.1480	0.276	0.228	✅
107	0.1524	0.250	0.250	✅
108	0.1500	0.290	0.215	✅
109	0.1540	0.295	0.207	✅

Aggregate results

Metric	Result
Evaluation seeds	10 (`100`–`109`)
Steps per seed	400
Mean reward per step	0.1478 ± 0.0036
Mean forward velocity	0.258 ± 0.028 m/s
Mean absolute velocity error	0.244 ± 0.027 m/s
Total terminations	0
Success rate without termination	100.0%

Raw, machine-readable results: evaluation.json and evaluation_by_seed.csv. No new video was generated because the policy did not change.

Files

policy.onnx — deployable policy with observation normalization
manifest.json — Microduck policy manifest
training_config.json — reproducibility settings
validation.json — release checks and hashes
render_metrics.json — finite-rollout reward, velocity, and termination summary
replay.mp4 — qualitative simulation result

Local inference

uv run scripts/infer_policy.py --walking policy.onnx --new-cmd-obs

References

Task: Robotics
Library: microduck
License: apache-2.0
Created: Sep 7, 2026
Updated: Sep 29, 2026