Abstract
AbstractSoft material robots are an emerging and fast‐growing field of research [1] with potential application in various technical fields. These applications include, but are not limited to medical applications and all sorts of human‐machine‐interaction. Due to the soft structure, conventional components and design methodologies are not applicable. For reliable control and positioning of soft robots in 3D space especially accurate knowledge about their current position and orientation is essential.In this contribution, a resistive curvature sensor for a soft robot is presented. It is based on electrically conductive foam attached to the soft robot. Deformations of the foam lead to a change in electrical resistance [2] which can be measured and used to determine the curvature of a soft robot. Since the sensor behavior is nonlinear and hysteretic, a neural network is used to determine the curvature of the soft robot from the measured foam resistances.
Highlights
Soft material robots are an emerging and fast-growing field of research [1] with potential application in various technical fields
A resistive curvature sensor for a soft robot is presented. It is based on electrically conductive foam attached to the soft robot
Since the sensor behavior is nonlinear and hysteretic, a neural network is used to determine the curvature of the soft robot from the measured foam resistances
Summary
Malte Grube1,∗ and Robert Seifried1,∗∗ 1 Hamburg University of Technology, Mechanics and Ocean Engineering, Eißendorfer Straße 42, 21073 Hamburg. Soft material robots are an emerging and fast-growing field of research [1] with potential application in various technical fields. These applications include, but are not limited to medical applications and all sorts of human-machine-interaction. For reliable control and positioning of soft robots in 3D space especially accurate knowledge about their current position and orientation is essential. In this contribution, a resistive curvature sensor for a soft robot is presented. Since the sensor behavior is nonlinear and hysteretic, a neural network is used to determine the curvature of the soft robot from the measured foam resistances
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