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NeatSkin: A Discrete Impedance Tomography Skin Sensor

Research output: Contribution to conferencePaper

Original languageEnglish
Number of pages6
DateAccepted/In press (current) - 6 Apr 2020
DatePublished - 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

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.

    Research areas

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

Event

Robosoft 2020: IEEE International Conference on Soft Robotics

Abbreviated titleRobosoft2020
Duration6 Apr 20209 Apr 2020
CityNew Haven
CountryUnited States
Web address (URL)
Degree of recognitionInternational event

Event: Conference

Documents

Documents

  • Full-text PDF (accepted author manuscript)

    Accepted author manuscript, 1.65 MB, PDF document

    Embargo ends: 9/04/20

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