Using Novel Multi-Frequency Analysis Methods to Retrieve Material and Temperature Information in Tactile Sensing Areas

Mehdi Abdelwahed (1) , Lounis Zerioul (1) , Alexandre Pitti (1) , Olivier Romain (1)

1 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes

This article presents a novel artificial skin technology based on the Electric Impedance Tomography (EIT) that employs multi-frequency currents for detecting the material and the temperature of objects in contact with piezoresistive sheets. To date, few artificial skins in the literature are capable of detecting an object’s material, e.g., wood, skin, leather, or plastic. EIT-based artificial skins have been employed mostly to detect the position of the contact but not its characteristics. Thanks to multi-frequency currents, our EIT-based artificial skin is capable of characterising the spectral profile of objects in contact and identifying an object’s material at ambient temperature. Moreover, our model is capable of detecting several levels of temperature (from −10 up to 60 °C) and can also maintain a certain accuracy for material identification. In addition to the known capabilities of EIT-based artificial skins concerning detecting pressure and location of objects, as well as being low cost, these two novel modalities demonstrate the potential of EIT-based artificial skins to achieve global tactile sensing.

Mots clés: tactile sensor; artificial skin; electrical impedance tomography; multi-frequencies; machine learning; material recognition; temperature

Domaines: Instrumentations et Détecteurs [physics.ins-det]

Mehdi Abdelwahed, Lounis Zerioul, Alexandre Pitti, Olivier Romain. Using Novel Multi-Frequency Analysis Methods to Retrieve Material and Temperature Information in Tactile Sensing Areas. Sensors, 2022, 22 (22), pp.8876. ⟨10.3390/s22228876⟩. ⟨hal-04003685⟩