Grey neural network-based forecasting system for vision-guided robot trajectory tracking

Shih-Hung Yang, Chung Hsien Chou, Chen Fang Chung, Wen Pang Pai, Tse Han Liu, Yung Sheng Chang, Jung Che Li, Huan Chan Ting, Yon Ping Chen

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

This paper presents a grey neural network-based forecasting system (GNNFS) in solving the prediction problem. GNNFS adopts a grey model to predict the signal and a neural network (NN) to forecast the prediction error of the grey model. A sequential batch learning (SBL) is developed to adjust the weights of the NN. The proposed GNNFS is applied to a binocular robot, called an Eye-Robot, for human-robot interaction which involved predicting the trajectory of a participant's hand and tracking the hand. By applying the SBL, the GNNFS can gradually learn to predict the trajectory of the hand and track it well. The experimental results show that the GNNFS can carry out the SBL in real-time for vision-guided robot trajectory tracking.

原文English
主出版物標題ICCAS 2011 - 2011 11th International Conference on Control, Automation and Systems
頁面1512-1517
頁數6
出版狀態Published - 2011 十二月 1
事件2011 11th International Conference on Control, Automation and Systems, ICCAS 2011 - Gyeonggi-do, Korea, Republic of
持續時間: 2011 十月 262011 十月 29

出版系列

名字International Conference on Control, Automation and Systems
ISSN(列印)1598-7833

Conference

Conference2011 11th International Conference on Control, Automation and Systems, ICCAS 2011
國家Korea, Republic of
城市Gyeonggi-do
期間11-10-2611-10-29

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

指紋 深入研究「Grey neural network-based forecasting system for vision-guided robot trajectory tracking」主題。共同形成了獨特的指紋。

引用此