--- 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 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}} } ```