Tactile Motion Recognition with Convolutional Neural Networks

被引：0

作者：

Wu, Haoying ^{[1
,2
]}

Jiang, Daimin ^{[2
]}

Gao, Hao ^{[2
]}

机构：

[1] Minist Educ, Key Lab Fiber Opt Sensing Technol & Informat Proc, Wuhan 430070, Hubei, Peoples R China

[2] Wuhan Univ Technol, Coll Informat Engn, Wuhan 430070, Hubei, Peoples R China

来源：

2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | 2017年

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To satisfy the diversity of tactile patterns during Physical Human Robot Interaction(PHRI), this paper proposes a method to recognize human tactile motion using a spherical handle equipped with tactile sensors. The method first exploits convolutional neural networks as universal feature extractors, and then support vector machines are implemented for classifying the 16 kinds of motion in 4D space. Experimental results show the superiority of our approach against other methods, leading to classification rates over 91.19%

引用

页码：1572 / 1577

页数：6

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