Instructions to use fffiloni/microduck-moonwalk-backward-55e6af with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Microduck
How to use fffiloni/microduck-moonwalk-backward-55e6af with Microduck:
# Replace SLOT with the slot specified in the model card (walk, stand, sitstand, ground_pick, kick_left, kick_right, roulade). sudo robotctl policy load SLOT fffiloni/microduck-moonwalk-backward-55e6af
- Notebooks
- Google Colab
- Kaggle
Moonwalk Backward โ Microduck policy
Generated with Microduck Motion Lab from Pollen Robotics' microduck_rl sim-to-real stack.
Prompt
Make Microduck perform a moonwalk-style backward gliding gait. It should move backward smoothly while alternating its feet, create the visual illusion of sliding rather than ordinary backward walking, keep its upper body stable and upright, avoid jumps or large vertical motion, maintain balance throughout, and finish in a stable standing pose after a few seconds.
Reproducibility
- Task:
Mjlab-MotionLabMoonwalkBackward-Flat-MicroDuck - Base recipe:
velocity microduck_rlrevision:d424a0c899f6b33cbd3daeb279913134349c0b63- Parallel environments: 4096
- PPO iterations: 4000
- Compiler:
recipe-plan-adapter-v0.10 - Final repo:
fffiloni/microduck-moonwalk-backward-55e6af
Deployment checks
- Official
scripts/export.py: passed - Shared actor observation contract: 61D
- Policy action output: 14D
- CPU MuJoCo/ONNX rehearsal: passed
- Automatic motion-quality gate: needs review
- Preview recipe: velocity
- Preview driver: velocity
- Semantic match unverified: True
- Maximum joint motion: 14.737863554636114ยฐ
- XY displacement: 0.33397904866706285 m
- Ball displacement: 0.0 m
Files
policy.onnxโ deployment policy exported by upstreamscripts/export.pypreview.mp4โ headless CPU MuJoCo deployment rehearsalthumbnail.webppreview_metrics.jsonmotion_spec.jsonresolved_plan.jsoncompiled_motion.jsontraining_result.jsoncheckpoints/model_final.pt
A simulation preview is not a guarantee of safe real-robot behavior. Validate conservatively before deploying to hardware.
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