A soft robotic hand: design, analysis, sEMG control, and experiment

被引:0
作者
Naishi Feng
Qiurong Shi
Hong Wang
Jiale Gong
Chong Liu
Zhiguo Lu
机构
[1] Northeastern University,Department of mechanical engineering and automation
来源
The International Journal of Advanced Manufacturing Technology | 2018年 / 97卷
关键词
Soft robot; sEMG; Three-segment cavity structure; Finite element analysis; Human-robot interaction;
D O I
暂无
中图分类号
学科分类号
摘要
Soft robot is a new type of flexible robot which can imitate human hand activity. Electromyographic (EMG) signal is an important bioelectrical signal associated with muscle activity. The innovative combination of soft robot and EMG shows great potential. Based on this inspiration, a humanoid soft robotic hand controlled by EMG was proposed. We designed a single finger 3D model for the soft robotic hand and put forward the three-stage cavity structure. The finite element analysis has been performed to obtain the influence of the geometrical parameters including the number of cavities, the shape of the cavity side section, and the pressure in the cavity on the single finger bending performance. The optimal geometrical parameters were obtained. We analyzed the geometrical deformation of the finger simulation model and figured out the relationship between the input pressure of the soft hand and the angle of bending deformation. In addition, we designed and manufactured the soft robotic hand model and its pneumatic system. Twenty-four effective eigenvalues were extracted from the surface EMG signal (sEMG) of the forearm muscle group and ten-kinds-gestures recognizing system was established. Finally, we realized the online sEMG control of the soft robotic hand, so that the soft robotic hand can reproduce the gestures behavior of human. The correct rate of recognition is 96%. Conclusions obtained in this paper provide theoretical support for the development of humanoid soft robotic hand.
引用
收藏
页码:319 / 333
页数:14
相关论文
共 49 条
[1]  
Rus D(2015)Design, fabrication and control of soft robots Nature 521 467-475
[2]  
Tolley MT(2016)Using voice coils to actuate modular soft robots: wormbot, an example Soft Robot 3 198-204
[3]  
Nemitz MP(2010)Stretchable electronics: materials strategies and devices & dagger Adv Mater 20 4887-4892
[4]  
Mihaylov P(2015)Soft and stretchable sensor using biocompatible electrodes and liquid for medical applications Soft Robot 2 146-154
[5]  
Barraclough TW(2015)Soft robotic glove for combined assistance and at-home rehabilitation Robot Auton Syst 73 135-143
[6]  
Ross D(2017)Automatic design of fiber-reinforced soft actuators for trajectory matching Proc Natl Acad Sci U S A 114 51-56
[7]  
Stokes AA(2003)SEMG evaluations: an overview Appl Psychophysiol Biofeedback 28 121-127
[8]  
Kim DH(1998)Variability of some SEMG parameter estimates with electrode location J Electromyogr Kinesiol Off J Int Soc Electrophysiol Kinesiol 8 305-315
[9]  
Rogers JA(2001)A wavelet-based continuous classification scheme for multifunction myoelectric control IEEE Trans Biomed Eng 48 302-311
[10]  
Russo S(2011)A neuro–fuzzy inference system for sEMG-based identification of hand motion commands NeuroImage 108 60-73