Directly printable flexible strain sensors for bending and contact feedback of soft actuators

  • Khaled Elgeneidy*
  • , Gerhard Neumann
  • , Michael Jackson
  • , Niels Lohse
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a fully printable sensorized bending actuator that can be calibrated to provide reliable bending feedback and simple contact detection. A soft bending actuator following a pleated morphology, as well as a flexible resistive strain sensor, were directly 3D printed using easily accessible FDM printer hardware with a dual-extrusion tool head. The flexible sensor was directly welded to the bending actuator's body and systematically tested to characterize and evaluate its response under variable input pressure. A signal conditioning circuit was developed to enhance the quality of the sensory feedback, and flexible conductive threads were used for wiring. The sensorized actuator's response was then calibrated using a vision system to convert the sensory readings to real bending angle values. The empirical relationship was derived using linear regression and validated at untrained input conditions to evaluate its accuracy. Furthermore, the sensorized actuator was tested in a constrained setup that prevents bending, to evaluate the potential of using the same sensor for simple contact detection by comparing the constrained and free-bending responses at the same input pressures. The results of this work demonstrated how a dual-extrusion FDM printing process can be tuned to directly print highly customizable flexible strain sensors that were able to provide reliable bending feedback and basic contact detection. The addition of such sensing capability to bending actuators enhances their functionality and reliability for applications such as controlled soft grasping, flexible wearables, and haptic devices.

Original languageEnglish
Article number2
JournalFrontiers Robotics AI
Volume5
Issue numberFEB
DOIs
Publication statusPublished - 2018

Bibliographical note

Publisher Copyright:
© 2018 Elgeneidy, Neumann, Jackson and Lohse.

Keywords

  • Grasping
  • Haptic feedback
  • Regression analysis
  • Soft actuators
  • Soft robotics
  • Soft sensors

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

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