Robot Skin with Touch and Bend Sensing using Electrical Impedance Tomography
Journal:
arXiv
Published Date:
Mar 17, 2025
Abstract
Flexible electronic skins that simultaneously sense touch and bend are
desired in several application areas, such as to cover articulated robot
structures. This paper introduces a flexible tactile sensor based on Electrical
Impedance Tomography (EIT), capable of simultaneously detecting and measuring
contact forces and flexion of the sensor. The sensor integrates a magnetic
hydrogel composite and utilizes EIT to reconstruct internal conductivity
distributions. Real-time estimation is achieved through the one-step
Gauss-Newton method, which dynamically updates reference voltages to
accommodate sensor deformation. A convolutional neural network is employed to
classify interactions, distinguishing between touch, bending, and idle states
using pre-reconstructed images. Experimental results demonstrate an average
touch localization error of 5.4 mm (SD 2.2 mm) and average bending angle
estimation errors of 1.9$^\circ$ (SD 1.6$^\circ$). The proposed adaptive
reference method effectively distinguishes between single- and multi-touch
scenarios while compensating for deformation effects. This makes the sensor a
promising solution for multimodal sensing in robotics and human-robot
collaboration.
