Toward Fingertip Non-Contact Material Recognition and Near-Distance Ranging for Robotic Grasping
Cheng Fang, Di Wang, Dezhen Song, Jun Zou
Abstract
We report the feasibility study of a new acoustic and optical bi-modal distance & material sensor for robotic grasping. The new sensor is designed to be mounted on the robot fingertip to provide last-moment perception before contact happens. It is based on both pulse-echo ultrasound and optoacoustic effects enabled by single-element air-coupled transducers. In contrast to conventional contact-based and recent pre-touch approaches, this new method overcomes their disadvantages and provides robotic fingers with the capability to detect the distance and material type of the target at a near distance before contact occurs, which is crucial for robust and nimble grasping. The proposed sensor has been tested with different materials, shapes, and porous properties. The experimental results show that this sensor design is functional and practical.
BibTeX
@inproceedings{icra2019_towardfingertipn,
title = {Toward Fingertip Non-Contact Material Recognition and Near-Distance Ranging for Robotic Grasping},
author = {Cheng Fang and Di Wang and Dezhen Song and Jun Zou},
booktitle = {ICRA 2019},
year = {2019}
}