Fingertip Non-Contact Optoacoustic Sensor for Near-Distance Ranging and Thickness Differentiation for Robotic Grasping
Cheng Fang, Di Wang, Dezhen Song, Jun Zou
Abstract
We report the feasibility study of a new optoacoustic sensor for both near-distance ranging and material thickness classification for robotic grasping. It is based on the optoacoustic effect where focused laser pulses are used to generate wideband ultrasound signals in the target. With a much smaller optical focal spot, the optoacoustic sensor achieves a lateral resolution of 93 μm, which is six times higher than ultrasound pulse-echo ranging under the same condition. A new multi-mode wideband PZT (lead zirconate titanate) transducer is built to properly receive the wideband optoacoustic signal. The ability to receive both low- and high-frequency components of the optoacoustic signal enhances the material sensing capability, which makes it promising to determine not only material type but also the sub-surface structures. For demonstration, optoacoustic spectra are collected from hard and soft materials with different thickness. A Bag-of-SFA-Symbols (BOSS) classifier is designed to perform primary material and then thickness classification based on the optoacoustic spectra. The accuracy of material / thickness classification reaches ≥ 99% and ≥ 94%, respectively, which shows the feasibility of differentiating solid materials with different thickness by the optoacoustic sensor.
BibTeX
@inproceedings{iros2020_fingertipnoncont,
title = {Fingertip Non-Contact Optoacoustic Sensor for Near-Distance Ranging and Thickness Differentiation for Robotic Grasping},
author = {Cheng Fang and Di Wang and Dezhen Song and Jun Zou},
booktitle = {IROS 2020},
year = {2020}
}