A Nonarray Soft Capacitive Tactile Sensor With Simultaneous Contact Force and Location Measurement for Intelligent Robotic Grippers

夹持器 电容感应 触觉传感器 接触力 接近传感器 声学 材料科学 机器人 电气工程 人工智能 计算机科学 工程类 机械工程 物理 量子力学
作者
Chao Tang,Xinxin Chang,Jinxing Wang,Yulian Peng,Houping Wu,Hongbo Wang
出处
期刊:IEEE Transactions on Instrumentation and Measurement [Institute of Electrical and Electronics Engineers]
卷期号:73: 1-9 被引量:32
标识
DOI:10.1109/tim.2023.3343795
摘要

Tactile sensing is essential for robotic manipulations and human–machine interactions. It is vital to provide contact location and force information between the robotic gripper and objects for safe and effective operation. Many existing tactile sensors deploy an array of sensing units for pressure mapping and contact location recognition. However, it is still challenging to utilize such array sensors in robotic grippers for real-world applications due to the complex wiring and electronics, high cost, and low reliability. In this work, we propose a nonarray soft tactile sensor (NA-STS) that utilizes two triangle textile electrodes and a rectangle electrode to form a pair of soft capacitive pressure sensors in a differential configuration along its length. The sum of the two capacitance variations represents the amplitude of the force, whereas the difference between them represents the contact location. A three-layer electrode, shielded soft tactile sensor with dimensions of$12\times60$mm was fabricated, characterized, and calibrated for simultaneous contact force and location measurement. The results show that the sensor can detect the force as low as 2.1 mN, with a range over 25 N, and a maximum error of 2.5 mm for contact location detection. In addition, the key design parameters of the NA-STS were investigated. Finally, two NA-STSs were integrated into a robotic gripper and demonstrated for monitoring the contact force and location during the gripping of various objects. The NA-STS has a simple structure, high performance, and rapid response and is easy-to-implement, immune to proximity effect, and robust for real-word applications.

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