Abstract

In this paper 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.
Original languageEnglish
Number of pages6
Publication statusPublished - 9 Apr 2020
EventRobosoft 2020: IEEE International Conference on Soft Robotics - New Haven, United States
Duration: 6 Apr 20209 Apr 2020
http://robosoft2020.org/

Conference

ConferenceRobosoft 2020
Abbreviated titleRobosoft2020
CountryUnited States
CityNew Haven
Period6/04/209/04/20
Internet address

Keywords

  • skin sensor
  • machine learning
  • soft robot
  • impedance tomography

Fingerprint Dive into the research topics of 'NeatSkin: A Discrete Impedance Tomography Skin Sensor'. Together they form a unique fingerprint.

  • Cite this