---
license: apache-2.0
task_categories:
  - robotics
tags:
  - LeRobot
  - yam
  - manipulation
  - bimanual
  - imitation-learning
configs:
  - config_name: default
    data_files: data/**/*.parquet
---

# abc_sort_legos_v21

Teleoperation dataset: **sort the legos into containers by color**

A **LeRobot v2.1** conversion of the `sort_the_legos_into_containers_by_color`
task from [XDOF/ABC-130k](https://huggingface.co/datasets/XDOF/ABC-130k),
prepared for fine-tuning [pi0.5](https://github.com/Physical-Intelligence/openpi)
(`pi05_base`) on the bimanual YAM platform.

## Dataset summary

| Field | Value |
|-------|-------|
| Robot | yam |
| Episodes | 500 (first 500 of 4,458 train episodes, sorted by episode uuid) |
| Total frames | 1,156,733 |
| FPS | 30 Hz |
| Task | sort the legos into containers by color |
| Format | LeRobot v2.1 |

## Is this 30 fps?

Yes — `meta/info.json` reports `fps: 30`, and every camera stream is encoded
at `video.fps: 30`. But note this is a **resampled** 30 fps, not a native
recording rate: in the source ABC-130k MCAP files, the action stream runs at
~200 Hz, state at ~265 Hz, and cameras at 30–60 Hz depending on station type
(each stream on its own independent clock). The conversion builds a fixed
30 Hz tick clock over the overlap window of all streams and does **causal
floor matching** (the latest message at or before each tick) to align
everything onto one common 30 Hz grid — actions are subsampled ~6.7:1, faster
cameras are decimated, and no stream runs below 30 Hz so frames are never
duplicated.

## Cameras

| Name |
|------|
| `head_camera` |
| `left_wrist_camera` |
| `right_wrist_camera` |

Video codec: h264, 640×480 (letterboxed, aspect-ratio preserved). Source
episodes come from two station types — RealSense (mono top camera) and ZED-X
(stereo top camera, one eye picked deterministically per episode) — both
handled by the same conversion.

## State space (`observation.state`, shape `[14]`)

| Index | Name |
|-------|------|
| 0 | `left_joint_0` |
| 1 | `left_joint_1` |
| 2 | `left_joint_2` |
| 3 | `left_joint_3` |
| 4 | `left_joint_4` |
| 5 | `left_joint_5` |
| 6 | `left_gripper` |
| 7 | `right_joint_0` |
| 8 | `right_joint_1` |
| 9 | `right_joint_2` |
| 10 | `right_joint_3` |
| 11 | `right_joint_4` |
| 12 | `right_joint_5` |
| 13 | `right_gripper` |

## Action space (`action`, shape `[14]`)

| Index | Name |
|-------|------|
| 0 | `left_joint_0` |
| 1 | `left_joint_1` |
| 2 | `left_joint_2` |
| 3 | `left_joint_3` |
| 4 | `left_joint_4` |
| 5 | `left_joint_5` |
| 6 | `left_gripper` |
| 7 | `right_joint_0` |
| 8 | `right_joint_1` |
| 9 | `right_joint_2` |
| 10 | `right_joint_3` |
| 11 | `right_joint_4` |
| 12 | `right_joint_5` |
| 13 | `right_gripper` |

State and action are 1:1 index-aligned. Joint values are absolute positions
in **radians**, base → wrist. Gripper is the normalized aperture from
ABC-130k (**0 = closed, 1 = open**). `action` holds the **commanded** joint
positions (source `/{side}-arm-action` + `/{side}-ee-action` topics);
`observation.state` holds the **measured** ones (`/{side}-arm-state` +
`/{side}-ee-state`). Both are absolute, not delta — pi0.5 applies
`DeltaActions` internally at train time.

## How this was converted

Source episodes are MCAP files (`episode.mcap` per episode). Conversion
script:
[`convert_abc_mcap_to_lerobot_v21.py`](https://github.com/Avant-US/openpi) —
`scripts/convert_abc_mcap_to_lerobot_v21.py`. See "Is this 30 fps?" above for
the resampling method.

`meta/episode_ids.json` maps each `episode_index` back to its original
ABC-130k episode uuid for traceability.

## Usage

```python
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

ds = LeRobotDataset("Sichang0621/abc_sort_legos_v21")
print(ds.num_episodes, ds.num_frames, ds[0]["observation.state"].shape)
```

## Attribution and license

This dataset is **derived from
[XDOF/ABC-130k](https://huggingface.co/datasets/XDOF/ABC-130k)** (Apache-2.0),
released alongside the ABC project ([abc.bot](https://abc.bot/),
[code](https://github.com/amazon-far/abc)). All robot trajectories and
imagery originate from ABC-130k; this repository contributes only the format
conversion described above. Please cite the ABC project when using this data.

Note that the upstream ABC-130k dataset is access-gated on the Hub. Licensed
under Apache-2.0, consistent with the source.

## License

Apache 2.0