A flexible capacitive tactile sensor array for prosthetic hand real-time contact force measurement

Author(s):  
Yancheng Wang ◽  
Kailun Xi ◽  
Guanghao Liang ◽  
Meqing Mei ◽  
Zichen Chen
2016 ◽  
Vol 28 (3) ◽  
pp. 378-385 ◽  
Author(s):  
Yancheng Wang ◽  
◽  
Kailun Xi ◽  
Deqing Mei ◽  
Guanhao Liang ◽  
...  

[abstFig src='/00280003/14.jpg' width=""300"" text='A wearable tactile sensor array for three-axis contact force measurement and slip detection in prosthetic hand grasping' ] Using INASTAMOR pressure-conductive rubber as the sensing material, we developed a flexible tactile sensor array to measure three-axis contact force and slip. The sensor array has 9 (3 × 3) sensing units, each consisting of three layers, i.e., a bottom electrode, conductive rubber chips, a top polydimethylsiloxane (PDMS) bump. We detailed the array’s structural design, working principle, and fabrication process. We also characterize the array’s three-axis force measurement performance. The full-scale force measurement ranges and sensitivities in <em>x</em>-, <em>y</em>-, and <em>z</em>-axes are characterized as 5, 5, 20 N and 0.675, 0.677, 0.251 V/N, respectively. The array is mounted on a prosthetic hand for detecting contact force and slip occurrence in grasping. Results showed that the array measures three-axis contact force and detects slippage by using discrete wavelet transformation. The tactile sensor array has potential applications in robot-hand grasping that require simultaneous slip detection and three-axis contact force measurement.


2013 ◽  
Vol 10 (03) ◽  
pp. 1350028 ◽  
Author(s):  
TING ZHANG ◽  
SHAOWEI FAN ◽  
LI JIANG ◽  
HONG LIU

This paper presents an anthropomorphic prosthetic hand, which has a thumb and four fingers, all the fingers of which are driven by servomotors built into the fingers and the palm. A novel flexible three-axis tactile sensor array have been investigated for their suitability to measure the grip forces exerted upon an object held by a prosthetic hand. The tactile sensor array are placed at the thumb of prosthetic hand with the capability of measuring both normal and shear force distribution using quantum tunneling composite (QTC) as a base material. A joystick-like mesa was attached to a sensor base to transfer external force, and there are four fan-shaped electrodes in a cell to decompose the contact force into normal and shear components. The sensor has been realized in a 2 × 6 array of unit sensors, and each unit sensor responds to normal and shear stresses in all three axes, respectively. The zero potential method is used to avoid crosstalk effect by setting all drive lines (row electrodes), which do not involve the measuring point at zero voltage and also by setting all output lines (column electrodes) at zero voltage. Measurement of a single sensor shows that the full-scale range of detectable force are about 10, 10 and 22 N for the x-, y- and z-directions, respectively. The sensitivities of a cell measured with a current setup are 0.47, 0.45 and 0.16 mV/mN for the x-, y- and z-directions, respectively. The sensor showed a high repeatability, low hysteresis, and min tactile cross-talk. The proposed flexible three-axial tactile sensor array can be applied in a curved or compliant surface that requires slip detection and flexibility, such as a prosthetic hand.


2021 ◽  
pp. 1-1
Author(s):  
Yi Gong ◽  
Xiaoying Cheng ◽  
Zhenyu Wu ◽  
Yisheng Liu ◽  
Ping Yu ◽  
...  

Machines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 119
Author(s):  
Tong Li ◽  
Xuguang Sun ◽  
Xin Shu ◽  
Chunkai Wang ◽  
Yifan Wang ◽  
...  

As an essential perceptual device, the tactile sensor can efficiently improve robot intelligence by providing contact force perception to develop algorithms based on contact force feedback. However, current tactile grasping technology lacks high-performance sensors and high-precision grasping prediction models, which limits its broad application. Herein, an intelligent robot grasping system that combines a highly sensitive tactile sensor array was constructed. A dataset that can reflect the grasping contact force of various objects was set up by multiple grasping operation feedback from a tactile sensor array. The stability state of each grasping operation was also recorded. On this basis, grasp stability prediction models with good performance in grasp state judgment were proposed. By feeding training data into different machine learning algorithms and comparing the judgment results, the best grasp prediction model for different scenes can be obtained. The model was validated to be efficient, and the judgment accuracy was over 98% in grasp stability prediction with limited training data. Further, experiments prove that the real-time contact force input based on the feedback of the tactile sensor array can periodically control robots to realize stable grasping according to the real-time grasping state of the prediction model.


Sensors ◽  
2016 ◽  
Vol 16 (6) ◽  
pp. 819 ◽  
Author(s):  
Ping Yu ◽  
Weiting Liu ◽  
Chunxin Gu ◽  
Xiaoying Cheng ◽  
Xin Fu

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