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Hauptverfasser: Su, Bo Ying, Wu, Yuchen, Wen, Chengtao, Liu, Changliu
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2404.15131
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author Su, Bo Ying
Wu, Yuchen
Wen, Chengtao
Liu, Changliu
author_facet Su, Bo Ying
Wu, Yuchen
Wen, Chengtao
Liu, Changliu
contents Tactile and textile skin technologies have become increasingly important for enhancing human-robot interaction and allowing robots to adapt to different environments. Despite notable advancements, there are ongoing challenges in skin signal processing, particularly in achieving both accuracy and speed in dynamic touch sensing. This paper introduces a new framework that poses the touch sensing problem as an estimation problem of resistive sensory arrays. Utilizing a Regularized Least Squares objective function which estimates the resistance distribution of the skin. We enhance the touch sensing accuracy and mitigate the ghosting effects, where false or misleading touches may be registered. Furthermore, our study presents a streamlined skin design that simplifies manufacturing processes without sacrificing performance. Experimental outcomes substantiate the effectiveness of our method, showing 26.9% improvement in multi-touch force-sensing accuracy for the tactile skin.
format Preprint
id arxiv_https___arxiv_org_abs_2404_15131
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimizing Multi-Touch Textile and Tactile Skin Sensing Through Circuit Parameter Estimation
Su, Bo Ying
Wu, Yuchen
Wen, Chengtao
Liu, Changliu
Robotics
Tactile and textile skin technologies have become increasingly important for enhancing human-robot interaction and allowing robots to adapt to different environments. Despite notable advancements, there are ongoing challenges in skin signal processing, particularly in achieving both accuracy and speed in dynamic touch sensing. This paper introduces a new framework that poses the touch sensing problem as an estimation problem of resistive sensory arrays. Utilizing a Regularized Least Squares objective function which estimates the resistance distribution of the skin. We enhance the touch sensing accuracy and mitigate the ghosting effects, where false or misleading touches may be registered. Furthermore, our study presents a streamlined skin design that simplifies manufacturing processes without sacrificing performance. Experimental outcomes substantiate the effectiveness of our method, showing 26.9% improvement in multi-touch force-sensing accuracy for the tactile skin.
title Optimizing Multi-Touch Textile and Tactile Skin Sensing Through Circuit Parameter Estimation
topic Robotics
url https://arxiv.org/abs/2404.15131