Datasets:
File size: 3,400 Bytes
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license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- robotics
- timeseries
- tsfile
- format:tsfile
modality:
- tabular
- timeseries
pretty_name: aloha_static_fork_pick_up TsFile
configs:
- config_name: default
data_files:
- split: train
path: data/aloha_static_fork_pick_up.tsfile
size_categories:
- 10K<n<100K
---
# aloha_static_fork_pick_up TsFile
This dataset is an Apache TsFile conversion of the Hugging Face dataset
[`lerobot/aloha_static_fork_pick_up`](https://huggingface.co/datasets/lerobot/aloha_static_fork_pick_up).
The source dataset was created with [LeRobot](https://github.com/huggingface/lerobot)
and is licensed under Apache 2.0.
Modalities: Time-series. The original visual MP4 streams remain available in
the source dataset; this repository stores the numeric robot state, effort,
action, frame metadata, task index, and episode tags as TsFile.
## Source Dataset
- Original dataset: [`lerobot/aloha_static_fork_pick_up`](https://huggingface.co/datasets/lerobot/aloha_static_fork_pick_up)
- Source task: `"Pick up the fork and place it on the plate."`
- Codebase version: LeRobot `v3.0`
- Robot type: `unknown`
- Split: `train` (`0:100`)
- Episodes: `100`
- Frames: `60,000`
- Sampling rate: `50 fps`
- Tasks: `1`
- Source data path: `data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet`
- Source video path: `videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4`
## Converted Files
- TsFile: `data/aloha_static_fork_pick_up.tsfile`
- Rows: `60,000`
- Table name: `aloha_static_fork_pick_up`
- Time precision: milliseconds
- Mirrored metadata: `meta/`, with `meta/info.json` updated for the TsFile artifact
## Schema
`Time` is generated as `round(timestamp * 1000)` milliseconds. Time restarts
within each episode, and devices are identified by the original LeRobot tag
columns.
- TAG columns: `episode_index`, `task_index`
- FIELD metadata columns: `frame_index`, `sample_index`, `next_done`
- FIELD vectors: `observation_state_0..observation_state_13`,
`observation_effort_0..observation_effort_13`, and `action_0..action_13`
The `next_done` field is stored as an INT64 flag: `0` means false and `1` means
true. The converted data has `100` true flags, one terminal frame per episode.
## Conversion Notes
- The source `timestamp` column is dropped after being mapped to `Time`; it is
recoverable as `Time / 1000` seconds.
- The source `index` column is renamed to `sample_index`.
- The source `next.done` column is renamed to `next_done` and stored as `0/1`
for stable TsFile readback.
- Vector columns are flattened by preserving the full source column name,
replacing `.` with `_`, and appending the element index.
- Source video features are not uploaded here:
`observation.images.cam_high`, `observation.images.cam_left_wrist`,
`observation.images.cam_low`, and `observation.images.cam_right_wrist`.
Use the original dataset's [`videos/`](https://huggingface.co/datasets/lerobot/aloha_static_fork_pick_up/tree/main/videos)
tree for the visual streams.
- Aside from the redundant `timestamp` column and omitted video files, no
numeric time-series rows are intentionally dropped.
## Read Example
```python
from tsfile import TsFileReader
path = "data/aloha_static_fork_pick_up.tsfile"
with TsFileReader(path) as reader:
tables = reader.get_all_table_schemas()
print(tables.keys())
```
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