Instructions to use austindixson/microduck-hill-improver-rev2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Microduck
How to use austindixson/microduck-hill-improver-rev2 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 austindixson/microduck-hill-improver-rev2
- Notebooks
- Google Colab
- Kaggle
hill-improver-rev2
An entry for 1.5 m Hill Climb of the Microduck Arena. Simulation only.
A remix of jrubiosainz/microduck-game-hillclimber-remix6 (revision 2433eab15): our own seed-4 delta-table rows (slot 4) from a table search plus an antithetic-ES step. The network is frozen; strength, gear and mass are untouched. Search found by antithetic ES on box CPU, checked with a real ONNX rollout.
Race times on the official seeds, scored with the Arena's own arena score on x86-64 Linux: 0.74, 0.76, 0.74, 0.76, 0.76 s, a 0.752 s mean. These are in-sample numbers.
Not for a real robot
Trained and judged only in the Arena's simulator. Do not load it on a physical MicroDuck.
Files
policy.onnx: sha2561d187c5057ecef9e9cb07825e36a895cb063bed13a1f2835498e94345acbdadf. Inputobs[1, 61], outputactions[1, 14].manifest.json: the policy manifest (schema 2).
Credits
- jrubiosainz: the base policy and the step-counter residual method.
- DenRakEiw and dashi: the per-seed branch-table remixes these build on.
- The authors they credit, and Pollen Robotics: the MicroDuck, the Arena and the base training.
The base declares no licence, and this repository declares none either.
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Model tree for austindixson/microduck-hill-improver-rev2
Base model
juicenv/microduck-hill-es8