A Bio‐Inspired Artificial Tactile Sensing System Based on Optical Microfiber and Enhanced by Neural Network

Author:

Weng Junjie12ORCID,Xiao Siyang12,Yu Yang1ORCID,Zhang Jianfa3,Chen Jian1,Wang Dongying1,Wang Zhencheng2,Liang Jianqiao12,Ma Hansi1,Yang Junbo1,Wang Tianwu4,Zhang Zhenrong12

Affiliation:

1. College of Sciences National University of Defense Technology Changsha 410073 China

2. School of Computer Electronic and Information Guangxi University Nanning 530004 China

3. Hunan Provincial Key Laboratory of Novel Nano‐Optoelectronic Information Materials and Devices National University of Defense Technology Changsha 410073 China

4. Great Bay Area Research Institute Aerospace Information Research Institute (AIR) of Chinese Academy of Science (CAS) Guangzhou 510700 China

Abstract

AbstractHuman tactile perception involves the activation of mechanoreceptors located within the skin in response to external stimuli, along with the organization and processing within the brain. However, human sensations may be subject to the issues related to some physiological factors (such as skin injury or neurasthenia), resulting in inability to quantify tactile information. To address this challenge, a novel bio‐inspired artificial tactile (BAT) sensing system enabled by the integration of optical microfiber (OM) with full‐connected neural network (FCNN) in this paper is demonstrated, inspired by human physiological characteristics and tactile mechanisms. In this system, the BAT sensor mimics human skin, where the OM serves as the mechanoreceptor for sensing tactile stimuli, while the FCNN functions as a simulated human brain to train and extract the signal characteristics for intelligent object recognition. The experimental results indicate that the proposed BAT sensor can sensitively respond to both the contact force (static tactile stimuli), as well as the vibrotactile events (dynamic tactile stimuli) for the recognition of regular textures. Furthermore, by integrating the trained FCNN, the BAT sensing system accurately identifies various intricate surface textures with an exceptional accuracy of 95.7%, highlighting its potential in next‐generation human‐machine interaction and advanced robotics.

Funder

National Key Research and Development Program of China

Program for New Century Excellent Talents in University

Natural Science Foundation of Hunan Province

National University of Defense Technology

China Postdoctoral Science Foundation

Science and Technology Planning Project of Guangdong Province

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3