Active Whisker-Inspired Food Material Surface Property Measurement Using Deep-Learned Mechanosensor

Abstract

Rat whiskers are an exceptional sensing system, extracting information from their surrounding environment. Inspired by this concept, active whisker sensors measure various physical and geometric properties through contact with objects. However, previous research has focused on measuring the object geometry, often overlooking the potential for broader applications of the sensors. Herein, an active whisker sensor that enables simple measurement of the surface properties such as surface hardness and adhesiveness is reported. Composed of motor-, wire-, and crack-based mechanosensor, the active whisker sensor implements a tapping process inspired by the movement of a rat's whiskers to quickly evaluate the object surface. One area of potential application is the food industry. The active whisker sensors offer a new approach to measuring surface properties of viscoelastic and inelastic food that are difficult to measure with traditional bulky systems. Herein, it is validated that the tapping process can be used to measure the surface properties of a various foods. With the aid of machine learning algorithms, sensor can also recognize differences in the surface properties of bananas at different ripeness stages and classify them with 99% accuracy. In this report, the possibilities for applications of active whisker sensors, including food industry, robotics, and medical devices, are opened up.