SkinCell: A Modular Tactile Sensor Patch for Physical Human–Robot Interaction

Abstract

In this article, we present the design, fabrication, integration, and performance evaluation of SkinCell sensors, a novel tactile array targeting human–robot interaction applications. A polyimide sheet is selected as the substrate of the sensor, and gold electrodes with circular interdigitated finger patterns are deposited through dc sputtering, creating a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> 4 sensor array with 16 tactile elements. Sensing elements are completed with a thin layer of spin-coated poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) organic polymer solution. Two individual sensor sheets are being laminated in a back-to-back fashion to create a half-Wheatstone-bridge configuration to reduce temperature coupling while improving sensitivity. The sensor array is then sandwiched between two layers of silicone elastomer with internal dimples and cavities to improve sensitivity, repeatability, and center of force detection resolution. A COMSOL simulation was performed to study the influence of adding the silicone encapsulation as well as design parameters to the sensor substrate. Our simulation results indicate an effective improvement of touch, i.e., voltage sensitivity by employing the featured encapsulation. Characterization experiments have been conducted to identify the sensitivity profile of each sensor on the array, which indicates an average sensitivity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$26.5~\mu $ </tex-math></inline-formula> V/N. In subsequent experiments, the calibration profiles are used to identify the resultant force during pressing, as well as the location of the center of pressure (COP) on the SkinCell sensor. Finally, SkinCell sensors have been integrated into the OctoCan, a structural electronic device that can acquire squeezing pressure data during physical human–robot interaction (pHRI).