A Recipe for Electrically-Driven Soft Robots via 3D Printed Handed Shearing Auxetics

Ryan L. Truby*, Lillian Chin, Daniela Rus

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Electrically-mediated actuation schemes offer great promise beyond popular pneumatic and suction based ones in soft robotics. However, they often rely on bespoke materials and manufacturing approaches that constrain design flexibility and widespread adoption. Following the recent introduction of a class of architected materials called handed shearing auxetics (HSAs), we present a 3D printing method for rapidly fabricating HSAs and HSA-based soft robots that can be directly driven by servo motors. To date, HSA fabrication has been limited to the laser cutting of extruded teflon tubes. Our work expands the HSA materials palette to include flexible and elastomeric polyurethanes. Herein, we investigate the influence of material composition and geometry on printed HSAs' mechanical behavior. In addition to individual HSA performance, we evaluate printed HSAs in two soft robotic systems - four degree-of-freedom (DoF) platforms and soft grippers - to confirm that printed HSAs perform similarly to the original teflon HSA designs. Finally, we demonstrate new soft robotic capabilities with 3D printed HSAs, including fully 3D printed HSA fingers, higher force generation in multi-DoF devices, and demonstrations of soft grippers with internal HSA endoskeletons. We anticipate our methods will expedite the design and integration of novel HSAs in electrically-driven soft robots and facilitate broader adoption of HSAs in the field.

Original languageEnglish (US)
Article number9326362
Pages (from-to)795-802
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume6
Issue number2
DOIs
StatePublished - Apr 2021
Externally publishedYes

Keywords

  • Soft robot materials and design
  • additive manufacturing
  • soft sensors and actuators

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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