---
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- VLA
- franka
- fr3
- real-robot
configs:
- config_name: default
  data_files: data/*/*.parquet
---

# TASL FR3 — 10-task real-robot manipulation dataset (video format)

Teleoperated (GELLO) demonstrations collected on a **Franka FR3 + Robotiq gripper**
bench at TASL, in **LeRobot v2.1** format. Used to LoRA fine-tune
[π0.5-DROID](https://github.com/Physical-Intelligence/openpi).

- **250 episodes** — exactly **25 per task**, 10 tasks
- **66,463 frames** @ 15 fps (~74 minutes of teleoperation)
- **2 camera views**, 224×224 RGB, stored as **h264 mp4** (500 videos)

> **This is the video-format copy**, made so the
> [LeRobot dataset visualizer](https://huggingface.co/spaces/lerobot/visualize_dataset)
> can open it (that viewer rejects image-only datasets). The image-in-parquet
> original — which is what the policy was actually trained on — lives at
> [`Litian2002/tasl-fr3-10task-250ep`](https://huggingface.co/datasets/Litian2002/tasl-fr3-10task-250ep).
> Frame data is identical; only the storage format differs.

## Tasks

| `task_index` | instruction |
|---|---|
| 0 | pick up the blue cup and place it into the red cup |
| 1 | stack the red block on top of the blue block |
| 2 | press the blue button |
| 3 | close the lid of the wooden shape sorter box |
| 4 | align the three colored blocks to the same orientation |
| 5 | rotate the red block so that it is perpendicular to the blue block |
| 6 | insert the orange block into the wooden shape sorter box |
| 7 | insert the book into the black book stand |
| 8 | pull the smaller book out of the black book stand |
| 9 | pull the small block out from under the large block |

## Columns

| column | shape / dtype | meaning |
|---|---|---|
| `observation.images.exterior` | 224×224×3 video | exterior camera (ZED 2i), looking at the table |
| `observation.images.wrist` | 224×224×3 video | wrist camera (ZED Mini, eye-in-hand) |
| `state` | float32 `[8]` | 7 joint angles + 1 gripper width |
| `actions` | float32 `[8]` | 7 joint velocities + 1 gripper command, normalized to [-1, 1] |
| `task_index` | int64 | index into `meta/tasks.jsonl` |
| `episode_index`, `frame_index`, `index`, `timestamp` | | standard LeRobot fields |
| `done`, `is_success`, `intervene_flag` | bool | **written by the collection stack but constant — carries no information** |

## Notes / caveats

- **No filtering was applied.** Every frame recorded during teleoperation is
  present; no idle-frame removal, no success filtering. Idle frames are
  effectively absent anyway (only 0.4% of frames have max |joint velocity| < 0.05).
- `is_success` and `intervene_flag` are `True` on **every** frame, so they cannot
  be used to select successful demonstrations.
- Episode lengths: min 4, 1st pct 124, median 248, 99th pct ~700, max 971 frames.
  **`episode_index=172` is only 4 frames long (0.3 s) and should be dropped.**
- The two camera images are a centre-square crop of a 1280×720 ZED frame,
  resized to 224 — roughly 56% of the original horizontal field of view.
- Collected 2026-08-16 and 2026-08-20.

## Loading

```python
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("Litian2002/tasl-fr3-10task-250ep")
```

Fine-tuned checkpoints trained on this dataset:
[`Litian2002/pi05-droid-franka-lora-10task`](https://huggingface.co/Litian2002/pi05-droid-franka-lora-10task)