Roulade

Roulade (poster)

An official Microduck move: Pollen Robotics' roulade, retrained from scratch by Microduck Academy with the upstream recipe as-is (task Mjlab-Roulade-Flat-MicroDuck of pollen-robotics/microduck_rl at 2b25a48, 5999 iterations, 4096 envs, no reward edit), so that it carries the base/model.pt checkpoint the Academy needs to remix it. The policy Pollen ships is roulade.onnx.

Pollen Robotics' roulade: a forward roll from standing, back on the feet in under a second, then the walk takes over.

Fidelity check (this move vs Pollen's policy, same scene, same command, take roll)

number this move Pollen's roulade.onnx
final_upright False True
max_tilt 1.0 1.0
base_z_mean 0.0787 0.1103
base_z_min 0.0426 0.0475
cum_forward_pitch_deg 306.9 342.0
z_max 0.1548 0.1775
upright_at_1s True True
head_contact_ticks 29 32
body_contact_ticks 72 14

Recorded with space/payload/render/rollout.py on the upstream robot MJCF (spikes/base_moves/fidelity.py). The roll itself matches Pollen's (cumulative forward pitch 307 vs 342 deg, upright at 1 s both). Pollen's roulade chains to the robot's stand slot at 1 s (chain: true); the retrained one is back on its feet by 0.85 s and the showcase take hands it to the base walk at 0.88 s (the manifest's duration_s, no chain): upright and still from 1.3 s, no second fall. Handed to Pollen's pollen-robotics/microduck-policies#alpha_stand.onnx at 1 s instead it tipped over once more before standing (the take shipped on 2026-09-14); left to run past 0.92 s on its own it rolls again and lies; Pollen's stands.

Run it on a robot

sudo robotctl policy add roulade tfrere/microduck-move-base-roulade
robotctl robot do roulade

Files

policy.onnx (play it, normalizer baked in), base/model.pt + base/agent.yaml + base/env.yaml (the rsl_rl checkpoint and configs: remix = fine-tune from it), rollouts/0.traj (trajectory.v1 showcase take, with the commands), video.mp4 + poster.jpg (the card clip), manifest.json (schema 2 + academy block: origin, source task and policy, training facts, fidelity numbers), fidelity.json, train.json.

Credits and license

The task, the reward design, the robot model and the training recipe are Pollen Robotics' work (pollen-robotics/microduck_rl, Apache-2.0). This repo republishes a retrained policy of that recipe under the same Apache-2.0 license, with the checkpoint, so the Academy's users can start from it.

Downloads last month

-

Downloads are not tracked for this model. How to track
Video Preview
loading