Intelligent computational control of multi-fingered dexterous robotic hand

Disi Chen; Gongfa Li; Guozhang Jiang; Yinfeng Fang; Zhaojie Ju; Honghai Liu

doi:10.1166/jctn.2015.4647

Intelligent computational control of multi-fingered dexterous robotic hand

Disi Chen
, Gongfa Li^*
, Guozhang Jiang
, Yinfeng Fang
, Zhaojie Ju
, Honghai Liu

^*Corresponding author for this work

Wuhan University of Science and Technology
University of Portsmouth

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

We discuss the intelligent computational control theory and introduce the hardware structure of HIT/DLR II dexterous robotic hand, which is the typical dexterous robotic hand. We show that how DSP or FPGA controller can be used in the dexterous robotic hand. A popular intelligent dexterous robotic hand control system, which named Electromyography (EMG) control is investigated. We introduced some mathematical algorithms in EMG controlling, such as Gauss mixture model (GMM), artificial neural network (ANN) and Support vector machine (SVM).

Original language	English
Pages (from-to)	6126-6132
Number of pages	7
Journal	Journal of Computational and Theoretical Nanoscience
Volume	12
Issue number	12
DOIs	https://doi.org/10.1166/jctn.2015.4647
State	Published - 2015
Externally published	Yes

Keywords

Dexterous hand
EMG control
Intelligent control

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10.1166/jctn.2015.4647

Cite this

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title = "Intelligent computational control of multi-fingered dexterous robotic hand",

abstract = "We discuss the intelligent computational control theory and introduce the hardware structure of HIT/DLR II dexterous robotic hand, which is the typical dexterous robotic hand. We show that how DSP or FPGA controller can be used in the dexterous robotic hand. A popular intelligent dexterous robotic hand control system, which named Electromyography (EMG) control is investigated. We introduced some mathematical algorithms in EMG controlling, such as Gauss mixture model (GMM), artificial neural network (ANN) and Support vector machine (SVM).",

keywords = "Dexterous hand, EMG control, Intelligent control",

author = "Disi Chen and Gongfa Li and Guozhang Jiang and Yinfeng Fang and Zhaojie Ju and Honghai Liu",

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year = "2015",

doi = "10.1166/jctn.2015.4647",

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T1 - Intelligent computational control of multi-fingered dexterous robotic hand

AU - Chen, Disi

AU - Li, Gongfa

AU - Jiang, Guozhang

AU - Fang, Yinfeng

AU - Ju, Zhaojie

AU - Liu, Honghai

PY - 2015

Y1 - 2015

N2 - We discuss the intelligent computational control theory and introduce the hardware structure of HIT/DLR II dexterous robotic hand, which is the typical dexterous robotic hand. We show that how DSP or FPGA controller can be used in the dexterous robotic hand. A popular intelligent dexterous robotic hand control system, which named Electromyography (EMG) control is investigated. We introduced some mathematical algorithms in EMG controlling, such as Gauss mixture model (GMM), artificial neural network (ANN) and Support vector machine (SVM).

AB - We discuss the intelligent computational control theory and introduce the hardware structure of HIT/DLR II dexterous robotic hand, which is the typical dexterous robotic hand. We show that how DSP or FPGA controller can be used in the dexterous robotic hand. A popular intelligent dexterous robotic hand control system, which named Electromyography (EMG) control is investigated. We introduced some mathematical algorithms in EMG controlling, such as Gauss mixture model (GMM), artificial neural network (ANN) and Support vector machine (SVM).

KW - Dexterous hand

KW - EMG control

KW - Intelligent control

UR - https://www.scopus.com/pages/publications/84979265961

U2 - 10.1166/jctn.2015.4647

DO - 10.1166/jctn.2015.4647

M3 - 文章

AN - SCOPUS:84979265961

SN - 1546-1955

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EP - 6132

JO - Journal of Computational and Theoretical Nanoscience

JF - Journal of Computational and Theoretical Nanoscience

IS - 12

ER -

Intelligent computational control of multi-fingered dexterous robotic hand

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Keywords

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