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Modelling dielectric elastomer circuit networks for soft biomimetics.

Luca Ciarella1, Katherine E Wilson1,2,3, A Richter1

  • 1Institute of Semiconductors and Microsystems, TU Dresden, 01062 Dresden, Germany.

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Summary

This study models soft electro-mechanical circuit networks using dielectric elastomers (DEs) for bio-inspired robots. The developed SIMULINK model accurately predicts DE circuit behavior, paving the way for advanced soft robotics.

Keywords:
SIMULINK modellingdielectric elastomer actuatorsdielectric elastomer electronicssoft biomimeticssoft circuit networks

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Area of Science:

  • Robotics and Materials Science
  • Soft Actuators and Electroactive Polymers

Background:

  • Fully soft electronic circuits are essential for creating entirely soft bio-inspired robots.
  • Dielectric elastomers (DEs) are versatile electroactive polymers capable of actuation, sensing, and energy harvesting.
  • Basic logic and memory functions have been demonstrated using DE actuators and switches.

Purpose of the Study:

  • To develop a comprehensive SIMULINK model for soft electro-mechanical circuit networks composed of DEs.
  • To integrate various mathematical models of DE behavior into a unified software representation.
  • To demonstrate the model's validity for complex DE circuit networks.

Main Methods:

  • Building a SIMULINK model incorporating the electro-mechanical behavior of DE logic units and their interconnections.
  • Integrating existing mathematical models for DEs, overcoming limitations of single-aspect conventional models.
  • Utilizing direct measurements to refine and validate the software representation of DE circuit networks.

Main Results:

  • A comprehensive SIMULINK model for DE circuit networks was successfully developed.
  • The model demonstrates qualitatively good prediction of device behavior, even with manual assembly variations.
  • The study validates a recently introduced model for DE behavior and applies it to more complex circuits.

Conclusions:

  • The developed model provides a robust software representation for DE circuit networks, essential for soft robotics.
  • Despite current limitations in manual fabrication, the model shows significant predictive capability.
  • Future improvements in materials and automated processes are expected to enhance model accuracy further.