| --- |
| 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. |
|
|
