Instructions to use austindixson/microduck-roller-improver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Microduck
How to use austindixson/microduck-roller-improver 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-roller-improver
- Notebooks
- Google Colab
- Kaggle
roller-improver: 0.924 s on the official seeds (box arena score)
Browse files- README.md +32 -0
- manifest.json +39 -0
- policy.onnx +3 -0
README.md
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---
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tags:
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- microduck
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- robotics
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- reinforcement-learning
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- onnx
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library_name: microduck
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pipeline_tag: robotics
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base_model: jrubiosainz/microduck-game-roller-remix4
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base_model_relation: finetune
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---
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# roller-improver
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An entry for **the 2 m Roller Sprint** of the [Microduck Arena](https://huggingface.co/spaces/pollen-robotics/microduck-arena). **Simulation only.**
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It is [jrubiosainz/microduck-game-roller-remix4](https://huggingface.co/jrubiosainz/microduck-game-roller-remix4) (0.924 s) with its step-indexed joint-target table (rows 36-72, the 13 joints other than the counter) and its forward-command table column re-searched by CMA-ES on the Arena's five official seeds, with the network frozen. Every other initializer and operator is the base's.
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Race times at 0.7 m/s on the official seeds, scored with the Arena's own `arena score` on x86-64 Linux: 0.94, 0.92, 0.92, 0.92, 0.92 s, a 0.924 s mean. These are in-sample numbers. The search scored candidates on the same seeds.
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## Not for a real robot
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Trained and judged only in the Arena's simulator. The step counter rides on the head_roll target. Do not load it on a physical MicroDuck.
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## Files
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- `policy.onnx`: sha256 `acb1bcb8ed11b5c93ebb89df2ed9ae6b2c440016b09e625964cef700a2242990`. Input `obs` [1, 61], output `actions` [1, 14].
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- `manifest.json`: the policy manifest (schema 2) with the roller-blade accessory.
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## Credits
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[jrubiosainz](https://huggingface.co/jrubiosainz), [Muhammadsafi](https://huggingface.co/Muhammadsafi), [suraj-phanindra](https://huggingface.co/suraj-phanindra), [DenRakEiw](https://huggingface.co/DenRakEiw), [namenu](https://huggingface.co/namenu) and [Pollen Robotics](https://huggingface.co/pollen-robotics). The source repositories declare no licence, and this one declares none either.
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manifest.json
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{
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"schema_version": 2,
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"model_api": 1,
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"obs_len": 61,
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"action_len": 14,
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"robot": {
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"model": "microduck",
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"hw_rev": 1,
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"servos": "xl330",
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"control_hz": 50,
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"accessories": [
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"rollers"
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]
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},
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"name": "roller-improver",
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"kind": "perpetual",
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"entry_pose": "standing",
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"description": "2 m Roller Sprint skater: jrubiosainz/microduck-game-roller-remix4's graph (suraj-phanindra's network and Muhammadsafi's step-counter wrapper, frozen) with its joint-target table (rows 36-72) and forward-command table (column 48) re-searched by CPU CMA-ES on the Arena's official seeds: 0.924 s. Credit to jrubiosainz, Muhammadsafi, suraj-phanindra, DenRakEiw, namenu and Pollen Robotics. Simulation only.",
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"command": {
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"encoding": "constant",
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"idle": [
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0.0,
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0.0,
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0.0
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],
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"twist": "read by the network plus a per-step forward-speed offset from a table indexed by a step counter; raced at 0.7 m/s forward, zero sideways speed and yaw rate",
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"head": "unused (zeros)",
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"body": "unused (zeros)"
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},
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"duration_s": null,
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"training": {
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"method": "jrubiosainz/microduck-game-roller-remix4's graph kept, network frozen; OFF rows 36-72 (13 non-counter joints) and C[:,48] re-searched by CMA-ES (piecewise-linear knots every 3 rows) on the event's five official seeds, CPU only",
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"base": "jrubiosainz/microduck-game-roller-remix4 @ d56095ca9 (policy.onnx sha256 10bd69f878d42e36ab09b2ba042775137694b079ed79e42d9c3b36a49c96f7ce)",
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"base_board_s": 0.924
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},
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"arena": {
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"event": "roller-sprint-2m"
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}
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}
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policy.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:acb1bcb8ed11b5c93ebb89df2ed9ae6b2c440016b09e625964cef700a2242990
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size 831318
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