用于滚动触觉感知的高保真、低成本视觉触觉传感器

IF 2.2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Sensors Letters Pub Date : 2024-10-09 DOI:10.1109/LSENS.2024.3477913
Lintao Xie;Guitao Yu;Tianhong Tong;Yang He;Dongtai Liang
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引用次数: 0

摘要

本文提出了一种低成本但高保真的滚动触觉系统,用于分辨曲面上的图案,包括一种改进的基于视觉的触觉传感器(VBTS)和一种新型轻量级处理框架。拟议的 VBTS 包含一个模块化环形照明配置和一个改进的传感弹性体,无需复杂加工即可轻松制造,总成本仅为 16.95 美元。为实现滚动触觉图像的实时数据处理,受基于事件的相机的启发,引入了基于计算机图形学的高效处理框架,该框架可将稀疏的滚动触觉图像整合为完整的高保真图像,以便进行最终分类。为了评估所提出系统的有效性,我们使用由 13 个具有相似纹理的圆柱体生成的数据集来训练分类模型,其中验证的识别准确率高达 98.3%。然后,我们对每个圆柱体样本进行了三次滚动触觉感知测试,平均在 1.2 秒内达到了 100% 的识别准确率,这表明所提出的感知系统具有良好的实时应用前景。
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A High-Fidelity, Low-Cost Visuotactile Sensor for Rolling Tactile Perception
In this letter, a low-cost but high-fidelity rolling tactile system is proposed for distinguishing patterns on curved surfaces, including an improved vision-based tactile sensor (VBTS) and a novel lightweight processing framework. The proposed VBTS contains a modular ring-shaped illumination configuration and an improved sensing elastomer, which is easy to fabricate without complex processing and costs only 16.95 USD in total. To achieve real-time data processing of rolling tactile images, inspired by event-based cameras, an efficient processing framework is introduced based on computer graphics, which can integrate sparse rolling tactile images into complete high-fidelity images for the final classification. To evaluate the effectiveness of the proposed system, a classification model is trained using a dataset generated by 13 cylinders with similar textures, where the identification accuracy of validation is up to 98.3%. Then, we test each cylinder sample for three rolling tactile perceptions and achieve 100% identification accuracy within 1.2 s on average, indicating a promising prospect of the proposed perception system for real-time application.
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来源期刊
IEEE Sensors Letters
IEEE Sensors Letters Engineering-Electrical and Electronic Engineering
CiteScore
3.50
自引率
7.10%
发文量
194
期刊最新文献
Front Cover IEEE Sensors Council Information Table of Contents IEEE Sensors Letters Subject Categories for Article Numbering Information IEEE Sensors Letters Publication Information
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