NeatSkin

In this paper with Euan Judd, we present NeatSkin, a novel artificial skin sensor based on electrical impedance tomography. The key feature is a discrete network of fluidic channels which is used to infer the location of touch. Change in resistance of the conductive fluid within these channels during deformation is used to construct sensitivity maps. We present a method to simulate touch using this unique network-based, low output dimensionality approach. The efficacy is demonstrated by fabricating a NeatSkin sensor. This paves the way for the development of more complex channel networks and a higher resolution soft skin sensor with potential applications in soft robotics, wearable devices and safe human-robot interaction

This work is now published in the IEEE International Conference on Soft Robotics, Robosoft 2020. Access the paper at the University of Bristol repository.

A video on the work is on Euan’s youtube channel. link