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Autori principali: S, Vishnu Rajendran, Mandil, Willow, Parsons, Simon, E, Amir Ghalamzan
Natura: Preprint
Pubblicazione: 2023
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Accesso online:https://arxiv.org/abs/2303.17355
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author S, Vishnu Rajendran
Mandil, Willow
Parsons, Simon
E, Amir Ghalamzan
author_facet S, Vishnu Rajendran
Mandil, Willow
Parsons, Simon
E, Amir Ghalamzan
contents This paper presents a novel soft tactile skin (STS) technology operating with sound waves. In this innovative approach, the sound waves generated by a speaker travel in channels embedded in a soft membrane and get modulated due to a deformation of the channel when pressed by an external force and received by a microphone at the end of the channel. The sensor leverages regression and classification methods for estimating the normal force and its contact location. Our sensor can be affixed to any robot part, e.g., end effectors or arm. We tested several regression and classifier methods to learn the relation between sound wave modulation, the applied force, and its location, respectively and picked the best-performing models for force and location predictions. Our novel tactile sensor yields 93% of the force estimation within 1.5 N tolerances for a range of 0-30+1 N and estimates contact locations with over 96% accuracy. We also demonstrated the performance of STS technology for a real-time gripping force control application.
format Preprint
id arxiv_https___arxiv_org_abs_2303_17355
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Acoustic Soft Tactile Skin (AST Skin)
S, Vishnu Rajendran
Mandil, Willow
Parsons, Simon
E, Amir Ghalamzan
Robotics
This paper presents a novel soft tactile skin (STS) technology operating with sound waves. In this innovative approach, the sound waves generated by a speaker travel in channels embedded in a soft membrane and get modulated due to a deformation of the channel when pressed by an external force and received by a microphone at the end of the channel. The sensor leverages regression and classification methods for estimating the normal force and its contact location. Our sensor can be affixed to any robot part, e.g., end effectors or arm. We tested several regression and classifier methods to learn the relation between sound wave modulation, the applied force, and its location, respectively and picked the best-performing models for force and location predictions. Our novel tactile sensor yields 93% of the force estimation within 1.5 N tolerances for a range of 0-30+1 N and estimates contact locations with over 96% accuracy. We also demonstrated the performance of STS technology for a real-time gripping force control application.
title Acoustic Soft Tactile Skin (AST Skin)
topic Robotics
url https://arxiv.org/abs/2303.17355