Grasping State Analysis of Soft Manipulator Based on Flexible Tactile Sensor Array
Haoyuan Wang, Hongge Ru, Hongliang Lei, Chi Zhang, Cheng Han, Hao Wu, Jian Huang
Abstract
Although the grasping state analysis is vital in the study of manipulators, the grasping state analysis of soft manipulators as an independent research topic is not much so far. This paper proposes a novel pneumatic soft manipulator with a flexible tactile sensor array (SM-FTSA). The flexible tactile sensor array comprises piezoresistive materials with a porous structure. An equal potential approach is adopted to realize the collection of tactile signals of the SM-FTSA. Inspired by the grasping analysis of rigid manipulators, we propose 4 grasping states for the SM-FTSA, including inflating, shaking, stable, and slipping. Based on the experimental data, we conduct grasping experiments on 12 objects with SM-FTSA, and we propose 10 features that reflect the grasping state. Several machine learning methods are utilized to classify the grasping state. Among them, the Random Forest method presents the best performance, and the average classification accuracy reaches 99%.
BibTeX
@inproceedings{iros2022_graspingstateana,
title = {Grasping State Analysis of Soft Manipulator Based on Flexible Tactile Sensor Array},
author = {Haoyuan Wang and Hongge Ru and Hongliang Lei and Chi Zhang and Cheng Han and Hao Wu and Jian Huang},
booktitle = {IROS 2022},
year = {2022}
}