| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: Ego-Tactile Manipulation |
| size_categories: |
| - 100K<n<1M |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - robotics |
| - physical-ai |
| - egocentric |
| - tactile |
| - manipulation |
| - action-segmentation |
| - multimodal |
| --- |
| |
| # Ego-Tactile Manipulation |
|
|
| *Egocentric video + dense two-hand tactile + touch-grounded action labels - by [**OpenGraph Labs**](https://www.opengraphlabs.com/).* |
|
|
| <video controls autoplay loop muted playsinline width="100%" src="https://huggingface.co/datasets/OpenGraphLabs-Research/ego-tactile-manipulation/resolve/main/assets/ego_tactile_grid.mp4"></video> |
|
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| <sub>Four episodes visualized in our dashboard - egocentric video with live tactile & sensor signals.</sub> |
|
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| Synchronized **ego + touch** human-manipulation data is rare. This is a clean **1.28-hour sample** from OpenGraph Labs' Physical-AI data pipeline: a head camera plus our **OGLO tactile gloves** on both hands, with action labels derived from the physical contact signal. |
|
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| ## OGLO - our tactile gloves |
|
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|  |
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| Worn on both hands · **5 fingers × 4×4 taxels = 80 channels per hand (160 total)** · 90 Hz pressure, co-registered to every video frame. |
|
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| ## Touch-grounded action segmentation |
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| Action boundaries come from physical **contact and grip-force** - no human ground truth. Concise labels are added within each physically-fixed span. |
|
|
|  |
|  |
|
|
| ## Specs |
|
|
| | | | |
| |---|---| |
| | Episodes / duration | 72 · **1.28 h** (138,629 frames @ 30 fps) | |
| | Camera | egocentric, 1920×1080 (intrinsics included) | |
| | Tactile | 160 channels · 30 Hz aligned + 90 Hz raw | |
| | IMU | head (9-ch) + both wrists (6-ch each) | |
| | Annotations | action / sub-action / anchor / grasp / hand / object (English) | |
| | Tasks | tabletop manipulation - pour, cap, cut, grip, arrange, … | |
| | License | CC-BY-4.0 | |
|
|
| ## What's inside |
|
|
| ``` |
| meta/ LeRobot v3.0 metadata (+ opengraph/: camera intrinsics, tactile highlights) |
| data/ per-frame parquet (tactile @30 Hz, IMU, annotations) |
| videos/ egocentric video |
| extra/ raw_tactile/ + raw_imu/ (head, both wrists) byte-exact raw sensors |
| rerun/ one .rrd per episode (instant visualization) |
| ``` |
|
|
| ## Format & use |
|
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| Packaged in **[LeRobot v3.0](https://huggingface.co/docs/lerobot)** and **[Rerun](https://rerun.io)**, so it's ready to use as-is: |
|
|
| ```python |
| from lerobot.datasets import LeRobotDataset |
| ds = LeRobotDataset("OpenGraphLabs-Research/ego-tactile-manipulation") |
| ``` |
| ```bash |
| rerun rerun/episode_000000.rrd # visualize an episode |
| ``` |
|
|
| ## About OpenGraph Labs |
|
|
| Physical-AI data infrastructure - we capture and post-process large-scale egocentric human manipulation data (multi-camera, tactile, IMU, metric egomotion, frame-level semantics). This is our first public sample; reach out for collaborations and larger releases. |
|
|
| 🌐 [opengraphlabs.com](https://www.opengraphlabs.com/) · 🤗 [OpenGraphLabs-Research](https://huggingface.co/OpenGraphLabs-Research) |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{opengraphlabs2026egotactile, |
| title = {Ego-Tactile Manipulation}, |
| author = {OpenGraph Labs}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/OpenGraphLabs-Research/ego-tactile-manipulation} |
| } |
| ``` |
|
|
| Released under **CC-BY-4.0** - free to use, including commercially, with attribution. |
|
|
