---
license: apache-2.0
task_categories: [robotics]
tags: [robotics, manipulation, benchmark, DOMINO, RoboTwin, reproducibility]
---

# DOMINO fixed-episode evaluation manifests

Pre-screened episode sets for the [DOMINO](https://github.com/H-EmbodVis/DOMINO) benchmark, `demo_clean_dynamic`, seed 0.

## Why

DOMINO's default protocol screens candidate seeds online with an RRT expert planner
until it finds 100 solvable episodes. That planner is **stochastic**, so two runs accept
different episode sets and two policies end up measured on different physics.

A manifest pins the accepted seeds **and** each episode's dynamic-motion state --
target object, start/end position, velocity vector, duration, and an RNG snapshot
(numpy, python, torch, torch_cuda). Every policy then sees identical episodes.

Producing these took roughly 12,414 expert-planner rollouts (~6 GPU-hours).

## Use

```bash
git clone https://github.com/H-EmbodVis/DOMINO.git && cd DOMINO

# --include is important: without it, this repo's own README.md would
# overwrite DOMINO's README.md in your clone.
hf download <REPO> --repo-type dataset --include 'eval_manifest/*' --local-dir .
# (huggingface_hub < 0.34 spells the command `huggingface-cli download`)

python script/eval_policy.py --config <deploy_policy.yml> --overrides \
    --task_name adjust_bottle --task_config demo_clean_dynamic \
    --episode_manifest eval_manifest/adjust_bottle/demo_clean_dynamic/seed0.pkl
```

`eval_policy.py` validates `task_name`, `task_config`, `embodiment`, `use_dynamic`,
`dynamic_level` and `dynamic_coefficient` against the manifest and refuses to run on a
mismatch, so a manifest cannot silently be paired with the wrong configuration.

## Provenance

- DOMINO commit: `22cd288865827cb932003c877cf2870fe5ca22e6`
- manifest `format_version`: 1
- embodiment: `['aloha-agilex']`
- `use_dynamic=True`, `dynamic_level=1`, `dynamic_coefficient=0.1`
- episodes per task: 100
- candidate seeds start at 100000

## Caveats

- Python **pickles** carrying numpy RNG state. Load with a compatible numpy (DOMINO pins 1.26.4). `EpisodeManifest.load` rejects any other `format_version`.
- Physics replay is **not bit-exact across machines**; mm-level contact differences remain. What these remove is episode-set drift and initial-state drift, the dominant variance sources.
- The `.json` beside each `.pkl` is a human-readable summary. Evaluation reads only the `.pkl`.

## Contents

35 tasks, 3,500 episodes, 12,414 candidate seeds screened (28% overall acceptance).

Sorted by acceptance rate -- low values mean the expert planner rarely solves that
scene, so those manifests were the expensive ones to produce.

| task | accepted | candidates | acceptance | seed range |
|---|---:|---:|---:|---|
| `put_object_cabinet` | 100 | 2004 | 5% | 100030–102003 |
| `scan_object` | 100 | 1335 | 7% | 100014–101334 |
| `place_bread_basket` | 100 | 1019 | 10% | 100003–101018 |
| `dump_bin_bigbin` | 100 | 780 | 13% | 100003–100779 |
| `move_playingcard_away` | 100 | 626 | 16% | 100003–100625 |
| `place_shoe` | 100 | 614 | 16% | 100000–100613 |
| `place_object_basket` | 100 | 419 | 24% | 100000–100418 |
| `place_bread_skillet` | 100 | 321 | 31% | 100002–100320 |
| `place_a2b_left` | 100 | 318 | 31% | 100004–100317 |
| `shake_bottle_horizontally` | 100 | 313 | 32% | 100004–100312 |
| `handover_block` | 100 | 299 | 33% | 100002–100298 |
| `shake_bottle` | 100 | 299 | 33% | 100000–100298 |
| `place_a2b_right` | 100 | 294 | 34% | 100002–100293 |
| `put_bottles_dustbin` | 100 | 271 | 37% | 100000–100270 |
| `place_can_basket` | 100 | 235 | 43% | 100002–100234 |
| `place_fan` | 100 | 228 | 44% | 100002–100227 |
| `beat_block_hammer` | 100 | 224 | 45% | 100003–100223 |
| `hanging_mug` | 100 | 224 | 45% | 100000–100223 |
| `handover_mic` | 100 | 223 | 45% | 100000–100222 |
| `grab_roller` | 100 | 197 | 51% | 100000–100196 |
| `move_can_pot` | 100 | 180 | 56% | 100000–100179 |
| `rotate_qrcode` | 100 | 178 | 56% | 100002–100177 |
| `adjust_bottle` | 100 | 172 | 58% | 100000–100171 |
| `click_alarmclock` | 100 | 171 | 58% | 100000–100170 |
| `stamp_seal` | 100 | 169 | 59% | 100000–100168 |
| `move_pillbottle_pad` | 100 | 157 | 64% | 100002–100156 |
| `place_mouse_pad` | 100 | 155 | 65% | 100000–100154 |
| `press_stapler` | 100 | 155 | 65% | 100000–100154 |
| `place_object_scale` | 100 | 137 | 73% | 100000–100136 |
| `place_phone_stand` | 100 | 128 | 78% | 100000–100127 |
| `place_container_plate` | 100 | 122 | 82% | 100000–100121 |
| `move_stapler_pad` | 100 | 119 | 84% | 100002–100118 |
| `place_empty_cup` | 100 | 117 | 85% | 100000–100116 |
| `place_object_stand` | 100 | 109 | 92% | 100000–100108 |
| `click_bell` | 100 | 102 | 98% | 100000–100101 |

## License

Apache-2.0, matching DOMINO. Please cite the DOMINO paper if you use these.