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基于纳米级柔性温压触觉传感器的多功能软体机器手指用于材料识别。

Multifunctional Soft Robotic Finger Based on a Nanoscale Flexible Temperature-Pressure Tactile Sensor for Material Recognition.

机构信息

State Key Laboratory of Precision Measuring Technology and Instruments, College of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin 300072, China.

出版信息

ACS Appl Mater Interfaces. 2021 Nov 24;13(46):55756-55765. doi: 10.1021/acsami.1c17923. Epub 2021 Nov 15.

Abstract

Robotic hands with tactile perception can perform more advanced and safer operations, such as material recognition. Nanowires with high sensitivity, fast response, and low power consumption are suitable for multifunctional flexible tactile sensors to provide the tactile perception of robotic hands. In this work, we designed a multifunctional soft robotic finger with a built-in nanoscale temperature-pressure tactile sensor for material recognition. The flexible multifunctional tactile sensor integrates a nanowire-based temperature sensor and a conductive sponge pressure sensor to measure the temperature change rate and contact pressure simultaneously. The developed nanoscale temperature and conductive sponge pressure sensor can reach a high sensitivity of 1.196%/°C and 13.29%/kPa, respectively. With this multifunctional tactile sensor, the soft finger can quickly recognize four metals within three contact pressure ranges and 13 materials within a high contact pressure range. By combining tactile information and artificial neural networks, the soft finger can recognize the materials precisely with a high recognition accuracy of 92.7 and 95.9%, respectively. This work proves the application potential of the multifunctional soft robot finger in material recognition.

摘要

具有触觉感知的机器人手可以执行更高级和更安全的操作,例如材料识别。具有高灵敏度、快速响应和低功耗的纳米线适合多功能柔性触觉传感器,为机器人手提供触觉感知。在这项工作中,我们设计了一种具有内置纳米级温度-压力触觉传感器的多功能软体机器人手指,用于材料识别。这种灵活的多功能触觉传感器集成了基于纳米线的温度传感器和导电海绵压力传感器,可同时测量温度变化率和接触压力。开发的纳米级温度和导电海绵压力传感器的灵敏度分别高达 1.196%/°C 和 13.29%/kPa。通过使用这种多功能触觉传感器,软体手指可以在三个接触压力范围内快速识别四种金属和在高接触压力范围内识别 13 种材料。通过结合触觉信息和人工神经网络,软体手指可以以 92.7%和 95.9%的高识别准确率精确识别材料。这项工作证明了多功能软体机器人手指在材料识别方面的应用潜力。

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