---
license: apache-2.0
authors:
- Andy Tang
task_categories:
- robotics
tags:
- LeRobot
- lego-atomic-step
- scripted
- simulation
- ur5
- v3
- blind
- tsfile
- timeseries
- tabular
- format:tsfile
modality:
- tabular
- text
- timeseries
pretty_name: Scripted Atomic Step Pose 0.6 TsFile
configs:
- config_name: default
  data_files:
  - split: train
    path: data/windfromthenorth_scripted_atomic_step_pose_0_6.tsfile
size_categories:
- 100K<n<1M
---

# Scripted Atomic Step Pose 0.6 TsFile

This Apache TsFile dataset is based on
[`windfromthenorth/scripted_atomic_step_pose_0.6`](https://huggingface.co/datasets/windfromthenorth/scripted_atomic_step_pose_0.6), a LeRobot
v2.1 simulation dataset containing UR5/WSG50 trajectories for placing a LEGO
brick on an assembly board.

## Source and Attribution

- Original dataset: [`windfromthenorth/scripted_atomic_step_pose_0.6`](https://huggingface.co/datasets/windfromthenorth/scripted_atomic_step_pose_0.6)
- Author and repository publisher: [Andy Tang (`windfromthenorth`)](https://huggingface.co/windfromthenorth)
- License: Apache-2.0
- Task: `place the lego brick on the assembly board`
- Robot type: `ur5_wsg50_lego_atomic_step`
- LeRobot version: `v2.1`
- Split: `train` (`0:955`)
- Sampling rate: 20 fps
- Scale: 955 episodes, 159,935 frames, 1 task, 955 source Parquet shards
- Source layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
- Paper, external homepage, and completed citation: not provided by the source card

The TsFile table is `windfromthenorth_scripted_atomic_step_pose_0_6` and contains 159,935 rows in
`data/windfromthenorth_scripted_atomic_step_pose_0_6.tsfile`. Source metadata is retained under `meta/`, with
`meta/info.json` updated for the TsFile table.

## Schema and Mapping

`Time = round(timestamp * 1000)` milliseconds. Time starts at zero and advances
in 50 ms steps within every episode.

| TsFile column | Role | Type | Source mapping |
|---|---|---|---|
| `Time` | TIME | TIMESTAMP | `round(timestamp * 1000)` ms |
| `episode_index` | TAG | STRING | Original INT64 episode index |
| `task_index` | TAG | STRING | Original INT64 task index |
| `frame_index` | FIELD | INT64 | Preserved |
| `sample_index` | FIELD | INT64 | Renamed from `index` |
| `action_0` ... `action_6` | FIELD | FLOAT | Flattened from `action[7]` |
| `observation_state_0` ... `observation_state_19` | FIELD | FLOAT | Flattened from `observation.state[20]` |

Dots in source names are replaced by underscores. The source `timestamp` is
not repeated because it is represented by `Time / 1000` seconds. The constant
`prompt` string is not stored as a measurement; its value remains in
`meta/tasks.jsonl`. No numeric row, episode, task, state dimension, or action
dimension is omitted.

## Videos

The original repository has no video location: its `meta/info.json` declares
`total_videos: 0` and `video_path: null`, and its remote file tree has no
`videos/` directory. Therefore this TsFile dataset contains no videos. The
numeric rows are indexed by `episode_index` and `frame_index` for any later
external alignment.

## Minimal Read Example

```python
from tsfile import TsFileReader

reader = TsFileReader("data/windfromthenorth_scripted_atomic_step_pose_0_6.tsfile")
with reader.query_table(
    "windfromthenorth_scripted_atomic_step_pose_0_6",
    ["episode_index", "task_index", "frame_index", "sample_index",
     "action_0", "observation_state_0"],
    batch_size=65536,
) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()
```

## Citation

The source card does not provide a paper or completed BibTeX entry. Cite the
original Hugging Face dataset and Andy Tang (`windfromthenorth`) when using
this dataset.