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大面积、低成本力/触觉电容传感器,适用于软体机器人应用。

Large-Area and Low-Cost Force/Tactile Capacitive Sensor for Soft Robotic Applications.

机构信息

Institut Pascal, Université Clermont Auvergne, Clermont Auvergne INP, CNRS, 63000 Clermont-Ferrand, France.

CiTIUS (Centro Singular de Investigación en Tecnoloxías Intelixentes), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.

出版信息

Sensors (Basel). 2022 May 27;22(11):4083. doi: 10.3390/s22114083.

Abstract

This paper presents a novel design and development of a low-cost and multi-touch sensor based on capacitive variations. This new sensor is very flexible and easy to fabricate, making it an appropriate choice for soft robot applications. Materials (conductive ink, silicone, and control boards) used in this sensor are inexpensive and easily found in the market. The proposed sensor is made of a wafer of different layers, silicone layers with electrically conductive ink, and a pressure-sensitive conductive paper sheet. Previous approaches like e-skin can measure the contact point or pressure of conductive objects like the human body or finger, while the proposed design enables the sensor to detect the object's contact point and the applied force without considering the material conductivity of the object. The sensor can detect five multi-touch points at the same time. A neural network architecture is used to calibrate the applied force with acceptable accuracy in the presence of noise, variation in gains, and non-linearity. The force measured in real time by a commercial precise force sensor (ATI) is mapped with the produced voltage obtained by changing the layers' capacitance between two electrode layers. Finally, the soft robot gripper embedding the suggested tactile sensor is utilized to grasp an object with position and force feedback signals.

摘要

本文提出了一种基于电容变化的低成本、多点触控传感器的新颖设计和开发。这种新型传感器非常灵活且易于制造,非常适合应用于软体机器人。这种传感器使用的材料(导电油墨、硅酮和控制板)价格低廉,且在市场上很容易找到。所提出的传感器由不同层的晶圆、带有导电油墨的硅酮层和压敏导电纸组成。像电子皮肤这样的先前方法可以测量人体或手指等导电物体的接触点或压力,而所提出的设计则可以在不考虑物体电导率的情况下检测物体的接触点和所施加的力。传感器可以同时检测五个多点触控点。使用神经网络架构来校准在存在噪声、增益变化和非线性的情况下的施加力,具有可接受的精度。通过改变两个电极层之间的层电容来获得产生的电压,并与通过商业精密力传感器 (ATI) 实时测量的力进行映射。最后,嵌入建议的触觉传感器的软体机器人夹爪用于抓取物体,并提供位置和力反馈信号。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2a9/9185300/8b189b084fcd/sensors-22-04083-g001.jpg

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