Soft Acoustic Curvature Sensor: Design and Development
Mohammad Sheikh Sofla, Hanita Golshanian, Vishnu Rajendran S, Amir Ghalamzan E
Abstract
This letter 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<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> for a range of 0 to 60 m<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> curvatures. These results demonstrate the effectiveness of the proposed method for estimating curvatures. With its flexible structure, SAC sensor holds potential for applications in soft robotics, including shape measurement for continuum manipulators, soft grippers, and wearable devices.
BibTeX
@inproceedings{ral2024_softacousticcurv,
title = {Soft Acoustic Curvature Sensor: Design and Development},
author = {Mohammad Sheikh Sofla and Hanita Golshanian and Vishnu Rajendran S and Amir Ghalamzan E},
booktitle = {RA-L 2024},
year = {2024}
}