microduck-rough-walk-e

rough-walk-e

Velocity-commanded walking tuned for rough ground (grid tiles, small stairs, rubble, slopes): the shipped alpha_walking fine-tuned 800 iterations on a hostile-terrain ladder. Same command scheme, same motor-power envelope, roughly half the falls.

<video controls muted loop src="https://huggingface.co/RemiFabre/microduck-rough-walk-e/resolve/main/media/preview.mp4" style="max-width:640px;width:100%"></video>

Command — twist slots of the 13-D command block (head / body slots: 4 head-joint deltas from HOME, rad (neck_pitch, head_pitch, head_yaw, head_roll) — tracked, same as alpha_walking, unused (zeros)); idle = [0, 0, 0]

What it does — drop-in replacement for alpha_walking: the same velocity-commanded walk (twist = [vx, vy, wz], head commands tracked), fine-tuned 800 iterations on a rough-terrain ladder (grid tiles, small stairs, rubble, slopes). Half the falls of alpha_walking on the rough-ground battery (14/110 vs 32/110), crosses 6–9° slopes and ±1.3 cm rubble it previously failed, at the same motor power (1.02 W vs 1.03 W on flat — same servo heating).

Limits (sim only, never run on hardware) — falls when descending steps ≥ 2 cm; push recovery slightly weaker than alpha_walking; on rubble bumps ≥ ~2 cm it steps in place instead of advancing; turn response is more linear than alpha's but tops out lower (0.41 rad/s achieved for 1.0 commanded).

Try it in simulation (laptop, no robot)

git clone -b hostile-terrain https://github.com/pollen-robotics/microduck_rl.git && cd microduck_rl && uv sync   # once
hf download RemiFabre/microduck-rough-walk-e policy.onnx --local-dir policies/rough-walk-e
uv run scripts/infer_policy.py --walking policies/rough-walk-e/policy.onnx        # Linux

On macOS the MuJoCo window needs mjpython (one-time libpython symlink, then):

ln -s "$(.venv/bin/python -c 'import sys; print(sys.base_prefix)')/lib/libpython3.12.dylib" .venv/libpython3.12.dylib
uv run mjpython scripts/infer_policy.py --walking policies/rough-walk-e/policy.onnx

Keys (in the launching terminal): arrows = velocity, A/E = turn, SPACE = coast, T = pause.

Try it on the robot — it is a walking policy: point the walk role at it, change nothing else. Keep the stock alpha_walking path noted somewhere so you can switch back in one edit.

scp policy.onnx radxa@<robot>:/home/radxa/policies/rough-walk-e/                   # 1. file on the robot
# 2. on the robot, in /etc/robot/robotd.toml:   [policy]  walk = "/home/radxa/policies/rough-walk-e/policy.onnx"
sudo systemctl restart robotd                                                      # 3. drive it exactly like alpha_walking

First hardware test suggestion: flat ground first (gait should feel like alpha), then a doormat/carpet edge, then a gentle ramp. It has never touched hardware.

Contract obs[1,61] f32 → actions[1,14] f32, normalizer baked in, 50 Hz, targets around HOME × 1.0. Kind perpetual, entry pose standing. Provenance Mjlab-Hostile-FinetuneFeetProgress-MicroDuck — pollen-robotics/microduck_rl @ 6cd45fc on branch hostile-terrain (https://github.com/pollen-robotics/microduck_rl/commit/6cd45fc), run pollen-robotics/hostile-e-finetune-feet-progress-20260830-0103 (resumed from alpha_walking's checkpoint, wandb yr25mna4 model_9999); exported with scripts/export.py. Files policy.onnx · manifest.json (all of the above, machine-readable) · media/preview.mp4 (sim rollout) Format: Microduck policy sharing.