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---
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- tactile
- so101
- paxini
configs:
- config_name: default
  data_files: data/*/*.parquet
language:
- en
pretty_name: SoTac
size_categories:
- 10K<n<100K

---

# SoTac — SO-101 Tactile Manipulation Corpus

SoTac is a growing corpus of visuo-tactile teleoperation demonstrations recorded on an
SO-101 arm with dual 3-axis tactile fingertip sensors. Every 30 Hz observation carries a
full per-taxel force map for both fingertips, and every episode ships with the raw
~91 Hz tactile stream as a sidecar — no downsampling at record time.

Created using [LeRobot](https://github.com/huggingface/lerobot) (via the
[lerobotac](https://github.com/Jingyi-Z/lerobotac) sensor fork).

<a class="flex" href="https://jingyi-z-lerobotac-dataset-visualizer.hf.space/Jingyi-Z/sotac/0">
<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/>
<img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/>
</a>

Use the button above — it opens the [LeRobotAC tactile visualizer](https://huggingface.co/spaces/Jingyi-Z/lerobotac-dataset-visualizer)
with per-taxel 3D force arrows, contact timelines, and the raw 91 Hz stream panels.
The standard LeRobot viewer does not render the tactile data.

## Contents

SoTac is actively growing — new tasks, objects, and sensors will be added over time.
This is the **curated** set: every episode was human-reviewed. Episodes with contact
faults (accidental gripper contact during approach, closed-finger approaches,
post-release contact), operator visibility, or sensor faults are removed, and idle
heads/tails are trimmed so every episode starts near task onset. The unedited archive
is [Jingyi-Z/sotac_raw](https://huggingface.co/datasets/Jingyi-Z/sotac_raw).

Current release (2026-08-26): 63 episodes / 25,401 frames (~14 min) across
3 pick-and-place tasks, grouped by task:

| task                                                         | episodes | episode # |
| ------------------------------------------------------------ | -------- | --------- |
| Pick up the red foam ball and place it into the container    | 21       | 0–20      |
| Pick up the orange rubber ball and place it into the container | 22       | 21–42     |
| Pick up the red cup and place it on top of the container     | 20       | 43–62     |

**Per-episode annotations** ship in `annotations/`:

- `episode_annotations.json`: episode-level curation labels — grasp type, attempt
  count, outcome (success / failure / partial), distractor objects (11 episodes
  include an orange ball or white box as distraction), grip-force quality labels
  (insufficient/excessive force), and free-form event notes.
- `episode_XXXXXX.json` (all 63 episodes): time-aligned language annotations —
  subtask segments (approach, grasp, transport, place_release) and tactile event
  interjections (contact, grasp_stable, slip, rotation, place, release/drop) with
  per-event confidence. Auto-generated from the 91 Hz tactile stream and
  human-reviewed in the visualizer.

**Stable provenance**: every episode carries a `source_raw_episode` field — both as a
column in `meta/episodes` and in the annotations — pointing to its index in
[sotac_raw](https://huggingface.co/datasets/Jingyi-Z/sotac_raw), which is append-only
and never renumbered. Curated releases may renumber freely; raw indices are the
permanent episode identity. `curation_map.json` in the root holds the full mapping.

Grip forces span gentle (~4–10 N peak) to firm (~50 N peak) handling across sessions.

**Data collection**: episodes 0–5 & 43–47 by Jingming Zhang, episodes 21–33 by
Yuzhou Wang, episodes 6–20, 34–42 & 48–62 by Jingyi Zou.

**Curation provenance**: derived from `sotac_raw` with
[`curate_tactile_dataset.py`](https://github.com/Jingyi-Z/lerobotac/blob/hall-sensor/curate_tactile_dataset.py)
and the spec `curation_sotac_v2.json` (same repo) — all deletions and per-episode
keep-windows are reproducible.

## Hardware

- **Robot**: SO-101 follower arm, teleoperated with an SO-101 leader arm
- **Cameras**: wrist + top, 640×480 @ 30 fps (MJPG)
- **Tactile**: 2× Paxini PX-6AX GEN3 (DP-S2015-Elite) fingertip pads on a shared
  High-Speed Communication Board — 52 taxels per pad, 3-axis force per taxel,
  0.1 N/LSB, ~91 Hz effective rate for both pads together. Firmware zeroing at
  connect. Finger `[0]` = gripper-side pad (module 10), finger `[1]` =
  wrist-roll-side pad (module 18).

## Data format

Standard [LeRobot](https://github.com/huggingface/lerobot) v3.0 dataset, plus one
extra feature and one extra directory:

**`observation.sensors.paxini_fingertip`** — float32, shape `(2, 52, 3)`:
the latest raw tactile sample per finger at each 30 Hz observation
(fingers × taxels × [fx, fy, fz], in units of 0.1 N). Per-taxel (x, y, z) mm
coordinates for the GEN3 layout are available in
[paxini-sdk](https://github.com/Jingyi-Z/paxini-sdk).

**`sensors/paxini_fingertip/episode_XXXXXX/`** — raw ~91 Hz stream sidecars:

- `sensor_1.csv`, `sensor_2.csv` (fingers 0 and 1): 163 columns —
  `timestamp_ns, frame_status, time_calibration_offset_ns, calibrated_timestamp_ns,
  fx, fy, fz, p_00_fx … p_51_fz` (resultant force followed by 52 per-taxel triplets)
- `alignment.json`: episode-start epoch timestamp (`time.time_ns`) anchoring the raw
  stream to frame 0 of the 30 Hz main table

## Collection protocol

Episodes start with the gripper open and the pads contact-free (calibration reference).
The operator and leader arm are kept out of both camera views where possible;
remaining appearances are flagged per-episode in the annotations. Object placement is
varied between episodes; some episodes include distractor objects.

## Tooling

- Recording: [lerobotac](https://github.com/Jingyi-Z/lerobotac) (`hall-sensor` branch) —
  LeRobot fork with a sensor framework; the `paxini` sensor's `combined` output mode +
  `record_raw_csv` produced this dataset
- Sensor SDK: [paxini-sdk](https://github.com/Jingyi-Z/paxini-sdk)
- Visualization / annotation: [LeRobotAC Dataset Visualizer](https://huggingface.co/spaces/Jingyi-Z/lerobotac-dataset-visualizer)

## Dataset Structure

[meta/info.json](meta/info.json):

```json
{
    "codebase_version": "v3.0",
    "fps": 30,
    "features": {
        "action": {
            "dtype": "float32",
            "names": [
                "shoulder_pan.pos",
                "shoulder_lift.pos",
                "elbow_flex.pos",
                "wrist_flex.pos",
                "wrist_roll.pos",
                "gripper.pos"
            ],
            "shape": [6]
        },
        "observation.state": {
            "dtype": "float32",
            "names": [
                "shoulder_pan.pos",
                "shoulder_lift.pos",
                "elbow_flex.pos",
                "wrist_flex.pos",
                "wrist_roll.pos",
                "gripper.pos"
            ],
            "shape": [6]
        },
        "observation.images.wrist": {
            "dtype": "video",
            "shape": [480, 640, 3],
            "names": ["height", "width", "channels"],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.images.top": {
            "dtype": "video",
            "shape": [480, 640, 3],
            "names": ["height", "width", "channels"],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.sensors.paxini_fingertip": {
            "dtype": "float32",
            "shape": [2, 52, 3],
            "names": ["finger", "taxel", "axis"]
        },
        "timestamp": {"dtype": "float32", "shape": [1], "names": null},
        "frame_index": {"dtype": "int64", "shape": [1], "names": null},
        "episode_index": {"dtype": "int64", "shape": [1], "names": null},
        "index": {"dtype": "int64", "shape": [1], "names": null},
        "task_index": {"dtype": "int64", "shape": [1], "names": null}
    },
    "total_episodes": 63,
    "total_frames": 25401,
    "total_tasks": 3,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 200,
    "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
    "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
    "robot_type": "so_sensor_follower",
    "splits": {
        "train": "0:63"
    }
}
```

## Citation

```bibtex
@misc{zou2026sotac,
  author       = {Zou, Jingyi},
  title        = {SoTac: An SO-101 Tactile Manipulation Corpus},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/datasets/Jingyi-Z/sotac}}
}
```