4.7 Article

Easy Integrability and Data Processing of a Soft Tactile Array Sensor Through Reconfiguration

期刊

IEEE SENSORS JOURNAL
卷 23, 期 7, 页码 7719-7727

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2023.3250947

关键词

Self-healing material; soft robotic interface; soft sensor; touch sensor

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To simplify the integration of soft tactile sensors, a new type of soft tactile array sensor is proposed, featuring sensitive keys made of different self-healing Diels-Alder (DA) conductive polymers. The optimization of key positions in the sensor array maximizes accuracy in detecting pressed key positions while minimizing the number of required wires. The use of reversible covalent bonds in the DA polymers allows for reconfiguration of the keys, enabling tailored tactile sensors for different applications.
Most soft tactile sensors require a large number of wires to read the sensed data and complex algorithms to treat them. This makes the integration of soft tactile sensors challenging in full robotic systems. In order to simplify the integration of those soft devices, a new type of soft tactile array sensor is proposed. The sensitive keys of the sensor are made of three different self-healing Diels-Alder (DA) conductive polymers. The key positions in the sensor array are optimized in order to maximize the sensor accuracy in detecting pressed key positions and limit the number of wires required to read the sensor data. Since DA polymers are used, the keys are robustly connected to each other, ensuring high interfacial strength and conductivity while allowing reconfiguration. The reversible covalent bonds of the DA polymer allow the keys to be cut and healed back together to reform another tactile sensor tailored for another application with full recovery of the initial mechanical and electrical properties. In this work, two study cases are investigated: a keypad and a position sensor. The novel soft tactile array could reach an accuracy as low as 1.31% for the keypad and 3.8% for the position sensor compared with the developed sensor model. The keypad has a 90% success rate, whereas the position sensor has a 64% success rate.

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