Human Action Imitation System Based on Nao Robot

被引：0

作者：

Hu, Ning ^{[1
,2
]}

Zheng, Lin ^{[1
,2
]}

机构：

[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan, Hubei, Peoples R China

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

来源：

PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年

关键词：

Nao robot; deep learning; image processing;

D O I：

10.1109/itnec.2019.8729383

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A human action imitation system based on Nao robot is proposed in this paper. A new strategy,combining Momentum with Stochastic gradient descent(SGD), is designed to accelerate the training process of Convolutional Neural Networks(CNN) . The CNN is used to recognize the 2D coordinate of joints of a human body. This data is translate to Nao Robot and make it to imitate human action.The experiments show that the training rate is faster than traditional training method. The Robot can imitate the human action accurately.

引用

页码：2261 / 2264

页数：4

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