Use of Multi-frequency Electrical Impedance Tomography as Tactile Sensor for Material Discrimination

Abstract

Electrical Impedance Tomography (EIT) is an imaging technique used recently as a tactile sensor. The advantages are the absence of electrodes within the sensor area, low-cost design and material. Moreover, it also includes low electric consumption and it can be shaped freely. Although EIT reconstruction gives a low spatial resolution, the retrieved impedance provides other information. Usually, frequencies in EIT are chosen to match specific impedance material. This paper proposes a new approach to retrieve the contact type as a new modality for tactile sensors. We propose to use Multi-Frequency Analysis (MFA) to retrieve the contact type. Our device uses the frequency range from 1k to 200k Hz. The results show the ability to classify 4 different types of material using clustering algorithms from raw data. This method is also able to differentiate hands from different people. MFA shows the use of multi-frequencies allows discriminating material. Furthermore, within one type of material, sight differences are also detectable. This new approach could lead to a cheap multi-modal sensor and allows better robotics arms manipulation.