Frontiers journals are at the top of citation and impact metrics

Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Robot. AI | doi: 10.3389/frobt.2019.00030

Design considerations for 3D printed, soft, multimaterial resistive sensors for soft robotics

 Benjamin Shih1,  Caleb Christianson1, Kyle Gillespie2,  Sebastian Lee1, Jason Mayeda1, Zhaoyuan Huo1 and  Michael T. Tolley1*
  • 1University of California, San Diego, United States
  • 2University of California, Los Angeles, United States

Sensor design for soft robots is a challenging problem because of the wide range of design parameters (e.g. geometry, material, actuation type, etc.) critical to their function. While conventional rigid sensors work effectively for soft robotics in specific situations, sensors that are directly integrated into the bodies of soft robots could help improve both their exteroceptive and interoceptive capabilities. To address this challenge, we designed sensors that can be co-fabricated with soft robot bodies using commercial 3D printers, without additional modification. We describe an approach to the design and fabrication of compliant, resistive soft sensors using a Connex3 Objet350 multimaterial printer and investigated an analytical comparison to sensors of similar geometries. The sensors consist of layers of commercial photopolymers with varying conductivities. We characterized the conductivity of TangoPlus, TangoBlackPlus, VeroClear, and Support705 materials under various conditions and demonstrate applications in which we can take advantage of these embedded sensors.

Keywords: Soft sensor, 3D printed, Soft skin, soft robotics, Resistive sensing, strain sensor

Received: 04 Dec 2018; Accepted: 08 Apr 2019.

Edited by:

Perla Maiolino, University of Cambridge, United Kingdom

Reviewed by:

Ioannis A. Ieropoulos, University of the West of England, United Kingdom
Josie Hughes, University of Cambridge, United Kingdom  

Copyright: © 2019 Shih, Christianson, Gillespie, Lee, Mayeda, Huo and Tolley. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Michael T. Tolley, University of California, San Diego, San Diego, 92093, California, United States, tolley@ucsd.edu