README.md

---
license: other
pretty_name: WorldArena Track1 RoboTwin Aloha-AgileX Clean 1500
language:
- en
task_categories:
- text-to-video
- robotics
tags:
- WorldArena
- RoboTwin2
- Aloha-AgileX
- robotics
- action-to-video
- ABot-PhysWorld
size_categories:
- 1K<n<10K
---

# WorldArena Track1 RoboTwin Aloha-AgileX Clean 1500

This dataset is a curated 1,500-episode RoboTwin2/Aloha-AgileX dual-arm gripper dataset prepared for WorldArena Track1-style ABot-PhysWorld SFT and A2V experiments.

It contains only the cleaned release artifacts. The original RoboTwin raw collection folders, HDF5 dumps, collection logs, smoke-test outputs, camera-debug grids, and training checkpoints are intentionally excluded.

## Summary

- Episodes: **1500**
- Embodiment: **Aloha-AgileX dual-arm gripper**
- Config: **wa_clean_fixed**, RT sample count 256 collection setting
- Video: **640x480 mp4**
- First frame: **320x240 png**
- Actions: `joint14`, normalized `joint14`, `ee16`, and `joint14+ee16`
- Camera: head camera, HDF5 verified for self-collected RoboTwin data
- SFT positives: **1500**
- A2V positives: **1500**
- Captions: short, WorldArena-style, and ABot-style dense captions

Trajectory length T:

- min: 76
- median: 191.0
- p95: 512.0
- max: 715

## Task Distribution

| task_family | count | percent |
|---|---:|---:|
| articulated_open_close | 130 | 8.7% |
| button_press_click | 150 | 10.0% |
| coverage_unknown | 100 | 6.7% |
| dumping_pouring | 60 | 4.0% |
| handover | 50 | 3.3% |
| hanging | 40 | 2.7% |
| lifting | 100 | 6.7% |
| object_to_container | 170 | 11.3% |
| pick_place | 180 | 12.0% |
| ranking_arrangement | 60 | 4.0% |
| rotation_orientation | 70 | 4.7% |
| scanning_qrcode | 80 | 5.3% |
| shaking | 70 | 4.7% |
| stacking | 120 | 8.0% |
| tool_use | 120 | 8.0% |

## Directory Structure

```text
episodes/rt_xxxxxx/
  observation.mp4
  first_frame.png
  action_joint14_raw.npy
  action_joint14_norm.npy
  action_ee16.npy
  action_joint14_ee16.npy
  camera_intrinsic.json
  camera_extrinsic.json
  camera_info.json
  meta.json
  quick_contact_sheet.jpg
  visual_sanity.json

manifests/
  episode_manifest.parquet
  episode_manifest.csv
  action_normalization_config.json
  worldarena_target_spec.yaml
  collection_job_summary.csv

sft_worldarena_style_caption_mix/metadata.jsonl
sft_pilot/train.jsonl
sft_pilot/val.jsonl
sft_pilot/fixed_eval.jsonl
a2v_worldarena_ee16_caption_mix/metadata.jsonl
captions_abot_style/
```

## Metadata Formats

SFT metadata lines:

```json
{"video":"episodes/rt_000000/observation.mp4","prompt":"...","episode_id":"rt_000000"}
```

A2V metadata lines:

```json
{"video":"episodes/rt_000000/observation.mp4","prompt":"...","action_path":"episodes/rt_000000/action_ee16.npy","intrinsic_path":"episodes/rt_000000/camera_intrinsic.json","extrinsic_path":"episodes/rt_000000/camera_extrinsic.json","original_size":[480,640]}
```

## Action Representation

- `action_joint14_raw.npy`: left arm 6 + left gripper 1 + right arm 6 + right gripper 1.
- `action_ee16.npy`: left xyz + left quaternion + left gripper + right xyz + right quaternion + right gripper.
- `action_joint14_ee16.npy`: concatenated 30D representation.
- Quaternion convention in A2V metadata: **wxyz**.
- EE local z offset used for action-map training/debug: **0.0**.
- Action-map convention: `robotwin_hdf5_z0`.

## Camera Convention

Camera source distribution:

```json
{
  "hdf5_verified": 1500
}
```

Embodiment distribution:

```json
{
  "aloha-agilex": 1500
}
```

For self-collected RoboTwin data, the camera convention is:

- camera: `head_camera`
- intrinsic: raw OpenCV K
- extrinsic: inverse of RoboTwin `observation/head_camera/extrinsic_cv`, exported as camera-to-world JSON for ABot/VACE utilities

## Recommended Usage

SFT:

```bash
DATASET_BASE_PATH=/path/to/this_dataset
DATASET_METADATA_PATH=$DATASET_BASE_PATH/sft_worldarena_style_caption_mix/metadata.jsonl
```

A2V ee16:

```bash
DATASET_BASE_PATH=/path/to/this_dataset
DATASET_METADATA_PATH=$DATASET_BASE_PATH/a2v_worldarena_ee16_caption_mix/metadata.jsonl
```

The A2V metadata is configured for ee16 with `quat_order=wxyz` and `ee_local_z_offset=0.0`.

## Notes and Limitations

- This is a generated RoboTwin2-style dataset intended for WorldArena Track1 experiments, not official WorldArena training data.
- The release excludes raw RoboTwin HDF5 and collection logs to keep the dataset compact.
- The dataset is focused on Aloha-AgileX dual-arm gripper manipulation and is not intended as a cross-embodiment dataset.
- Use the included manifests and camera/action metadata when training ABot-PhysWorld A2V models.