A Pretouch Perception Algorithm for Object Material and Structure Mapping to Assist Grasp and Manipulation Using a DMDSM Sensor
Fengzhi Guo, Shuangyu Xie, Di Wang, Cheng Fang, Jun Zou, Dezhen Song
Abstract
We report a new material and structure mapping (MSM) algorithm to assist robotic grasping and manipulation. Building on our new sensor development, the algorithm has four main components: 1) detection of time-of-flight (ToF) durations for the dual modalities of optoacoustic (OA) and pulse-echo ultrasound (US), 2) contour reconstruction by fusing OA and US signals, 3) local noise filtering by checking local consistency of material and structure label (MSL), and 4) medium boundary searching that identifies class boundaries through two-staged clustering and boundary establishment using support vector machine (SVM) hyperplanes. We have implemented our algorithm and tested it with multiple common household items. The experimental results have successfully validated our algorithm design which shows that the average error of contour reconstruction is 0.05 mm and the true positive rate of MSL is over 98%.
BibTeX
@inproceedings{iros2023_apretouchpercept,
title = {A Pretouch Perception Algorithm for Object Material and Structure Mapping to Assist Grasp and Manipulation Using a DMDSM Sensor},
author = {Fengzhi Guo and Shuangyu Xie and Di Wang and Cheng Fang and Jun Zou and Dezhen Song},
booktitle = {IROS 2023},
year = {2023}
}