基于FBG的机器手指尖触觉感知研究  

Research on tactile perception of machine fingertip based on FBG

作　　者：孙世政[1] 何江 秦鸿宇 徐向阳[1] 陈仁祥 Sun Shizheng;He Jiang;Qin Hongyu;Xu Xiangyang;Chen Renxiang(School of Mechatronics and Vehicle Engineering,Chongqing Jiaotong University,Chongqing 400074,China)

机构地区：[1]重庆交通大学机电与车辆工程学院,重庆400074

出　　处：《仪器仪表学报》2024年第5期72-81,共10页Chinese Journal of Scientific Instrument

基　　金：国家自然科学基金青年科学基金(52105542);重庆市自然科学基金创新发展联合基金(CSTB2023NSCQ-LZX0081);重庆市教育委员会科学技术研究项目(KJZD-K202200705);重庆市技术创新与应用发展专项重大项目(CSTB2023TIAD-STX0016)资助。

摘　　要：为了提高机器手指尖触觉感知灵敏度和精度,基于机器手指尖触觉感知机理分析,设计了特征分离式双层“十字”型FBG触觉感知单元,并进行了有限元仿真分析,针对感知单元开展了标定实验和抓握感知实验。基于接触温度和抓握力复合感知进行了耦合分析,提出了基于鲸鱼优化算法优化BP神经网络(WOA-BPNN)的解耦方法。实验结果表明:FBG感知单元的接触温度灵敏度为11.255 pm/℃,抓握力灵敏度为17.342 nm/MPa;WOA-BP解耦模型的接触温度平均绝对误差减小了72.53%,抓握力平均绝对误差减小了68.55%。In order to improve the sensitivity and accuracy of the tactile perception of the fingertip of the machine,based on the analysis of the mechanism of the fingertip tactile perception machine,a feature-separated double-layer“cross”-type FBG tactile sensing unit was designed,and finite-element simulation analysis was carried out,and calibration experiments and grip sensing experiments were carried out for the sensing unit.Based on the composite perception of contact temperature and grip force,a coupling analysis was carried out,and a decoupling method based on whale optimization algorithm for optimising back propagation neural network(WOA-BPNN)is proposed.The experimental results show that the contact temperature sensitivity of the FBG sensing unit is 11.255 pm/℃,and the grip force sensitivity is 17.342 nm/MPa;the average absolute error of the contact temperature of the WOA-BP decoupling model is reduced by 72.53%,and the average absolute error of the grip force is reduced by 68.55%.

关 键 词：FBG 机器手指尖 触觉 WOA-BP解耦模型 

分 类 号：TH741[机械工程—光学工程] TN247[机械工程—仪器科学与技术]