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3D printed resistive soft sensors

Authors: Benjamin Shih; Jason Mayeda; Zhaoyuan Huo; Caleb Christianson; Michael Thomas Tolley;

3D printed resistive soft sensors

Abstract

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 are effective for soft robotics in specific situations, sensors that are directly integrated into the bodies of soft robots could help improve both their exteroception and interoception capabilities. To address this challenge, we seek to design 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, and present characterizations for linear, planar, and 3D sensors. The sensors consist of layers of nonconductive and conductive commercial photopolymers that the printer cures with UV light. We demonstrate the capabilities of our method by printing linear and multilayer soft sensors, and by embedding non-planar heart- and brain-shaped sensors within a humanoid shape, which enables the humanoid to detect contact with its environment. Please see the video for additional details.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Top 10%
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