Digger Finger: GelSight Tactile Sensor
A miniature wedge-shaped GelSight visual-tactile sensor specialized for identifying objects buried in granular media. Published at ISER 2020. Featured on MIT News.
Radhen Patel, Nancy Ouyang, Branden Romero, Edward Adelson
International Symposium on Experimental Robotics, 2020
GelSights are visual-tactile sensors that give robots a sense of touch by capturing high-resolution surface geometry via a camera embedded in a soft gel fingertip. This work designed a novel miniature wedge-shaped GelSight — the Digger Finger — customized for a specific application: identifying objects buried underground in sand and other granular media.
I helped prototype the physical sensor design and developed the initial shape detection and annotation algorithm, which used a YOLO-OBB model to classify objects from the tactile images captured while the finger digs through granular material.
The project was featured on MIT News in May 2021.