Soft Acoustic Curvature Sensor: Design and Development

Fuente: arXiv
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Auteurs principaux: Sofla, Mohammad Sheikh, Golshanian, Hanita, S, Vishnu Rajendran, E, Amir Ghalamzan
Format: Preprint
Publié: 2024
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author Sofla, Mohammad Sheikh
Golshanian, Hanita
S, Vishnu Rajendran
E, Amir Ghalamzan
author_facet Sofla, Mohammad Sheikh
Golshanian, Hanita
S, Vishnu Rajendran
E, Amir Ghalamzan
contents This paper introduces a novel Soft Acoustic Curvature (SAC) sensor. SAC incorporates integrated audio components and features an acoustic channel within a flexible structure. A reference acoustic wave, generated by a speaker at one end of the channel, propagates and is received by a microphone at the other channel's end. Our previous study revealed that acoustic wave energy dissipation varies with acoustic channel deformation, leading us to design a novel channel capable of large deformation due to bending. We then use Machine Learning (ML) models to establish a complex mapping between channel deformations and sound modulation. Various sound frequencies and ML models were evaluated to enhance curvature detection accuracy. The sensor, constructed using soft material and 3D printing, was validated experimentally, with curvature measurement errors remaining within 3.5 m-1 for a range of 0 to 60 m-1 curvatures. These results demonstrate the effectiveness of the proposed method for estimating curvatures. With its flexible structure, the SAC sensor holds potential for applications in soft robotics, including shape measurement for continuum manipulators, soft grippers, and wearable devices.
format Preprint
id arxiv_https___arxiv_org_abs_2409_06395
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Soft Acoustic Curvature Sensor: Design and Development
Sofla, Mohammad Sheikh
Golshanian, Hanita
S, Vishnu Rajendran
E, Amir Ghalamzan
Sound
Robotics
Audio and Speech Processing
This paper introduces a novel Soft Acoustic Curvature (SAC) sensor. SAC incorporates integrated audio components and features an acoustic channel within a flexible structure. A reference acoustic wave, generated by a speaker at one end of the channel, propagates and is received by a microphone at the other channel's end. Our previous study revealed that acoustic wave energy dissipation varies with acoustic channel deformation, leading us to design a novel channel capable of large deformation due to bending. We then use Machine Learning (ML) models to establish a complex mapping between channel deformations and sound modulation. Various sound frequencies and ML models were evaluated to enhance curvature detection accuracy. The sensor, constructed using soft material and 3D printing, was validated experimentally, with curvature measurement errors remaining within 3.5 m-1 for a range of 0 to 60 m-1 curvatures. These results demonstrate the effectiveness of the proposed method for estimating curvatures. With its flexible structure, the SAC sensor holds potential for applications in soft robotics, including shape measurement for continuum manipulators, soft grippers, and wearable devices.
title Soft Acoustic Curvature Sensor: Design and Development
topic Sound
Robotics
Audio and Speech Processing
url https://arxiv.org/abs/2409.06395