GelSight Tactile Datasets
High-resolution vision-based touch sensing data from MIT CSAIL. See what robots feel.
Research Only
Images + Force Data
Tactile Sensing
Overview
GelSight is a family of vision-based tactile sensors developed at MIT CSAIL that use a camera behind a soft elastomer membrane to produce high-resolution images of surface contact. When the sensor presses against an object, the membrane deforms and the camera captures detailed geometry of the contact patch -- including surface normals, texture, and deformation patterns.
Several research datasets have been released using GelSight sensors, covering applications including:
- Grasp stability prediction: Predicting whether a grasp will succeed from initial tactile contact
- Texture and material classification: Identifying materials by touch
- Slip detection: Detecting incipient slip during manipulation
- Contact geometry reconstruction: Recovering 3D surface geometry from tactile images
- Cable manipulation: Tactile-guided deformable object manipulation
Access
Note: Most GelSight datasets are released for academic research only. Contact MIT CSAIL for commercial licensing.
Related datasets
- Touch and Go -- paired vision-tactile cross-modal data
- RH20T -- multi-modal manipulation including 200Hz tactile
- DROID -- visual manipulation at scale