A fabrication strategy for millimeter-scale, self-sensing soft-rigid hybrid robots
Hun Chan Lee,
Nash Elder,
Matthew Leal,
Sarah Stantial,
Elenis Vergara Martinez,
Sneha Jos,
Hyunje Cho and
Sheila Russo ()
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Hun Chan Lee: Boston University
Nash Elder: Boston University
Matthew Leal: Boston University
Sarah Stantial: Boston University
Elenis Vergara Martinez: Florida International University
Sneha Jos: Boston University
Hyunje Cho: Boston University
Sheila Russo: Boston University
Nature Communications, 2024, vol. 15, issue 1, 1-16
Abstract:
Abstract Soft robots typically involve manual assembly of core hardware components like actuators, sensors, and controllers. This increases fabrication time and reduces consistency, especially in small-scale soft robots. We present a scalable monolithic fabrication method for millimeter-scale soft-rigid hybrid robots, simplifying the integration of core hardware components. Actuation is provided by soft-foldable polytetrafluoroethylene film-based actuators powered by ionic fluid injection. The desired motion is encoded by integrating a mechanical controller, comprised of rigid-flexible materials. The robot’s motion can be self-sensed using an ionic resistive sensor by detecting electrical resistance changes across its body. Our approach is demonstrated by fabricating three distinct soft-rigid hybrid robotic modules, each with unique degrees of freedom: translational, bending, and roto-translational motions. These modules connect to form a soft-rigid hybrid continuum robot with real-time shape-sensing capabilities. We showcase the robot’s capabilities by performing object pick-and-place, needle steering and tissue puncturing, and optical fiber steering tasks.
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51137-8
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DOI: 10.1038/s41467-024-51137-8
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