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.
Four episodes visualized in our dashboard - egocentric video with live tactile & sensor signals.
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.
OGLO - our tactile gloves
Worn on both hands · 5 fingers × 4×4 taxels = 80 channels per hand (160 total) · 90 Hz pressure, co-registered to every video frame.
Touch-grounded action segmentation
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
Packaged in LeRobot v3.0 and Rerun, so it's ready to use as-is:
from lerobot.datasets import LeRobotDataset
ds = LeRobotDataset("OpenGraphLabs-Research/ego-tactile-manipulation")
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 · 🤗 OpenGraphLabs-Research
Citation
@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.