@inproceedings{69451f8b4835467e95988a1ce6ad9967,
title = "Grey neural network-based forecasting system for vision-guided robot trajectory tracking",
abstract = "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.",
keywords = "Grey model, learning, neural network, prediction, robot",
author = "Yang, {Shih Hung} and Chou, {Chung Hsien} and Chung, {Chen Fang} and Pai, {Wen Pang} and Liu, {Tse Han} and Chang, {Yung Sheng} and Li, {Jung Che} and Ting, {Huan Chan} and Yon-Ping Chen",
year = "2011",
month = oct,
day = "26",
language = "English",
isbn = "9781457708350",
series = "International Conference on Control, Automation and Systems",
pages = "1512--1517",
booktitle = "ICCAS 2011 - 2011 11th International Conference on Control, Automation and Systems",
note = "2011 11th International Conference on Control, Automation and Systems, ICCAS 2011 ; Conference date: 26-10-2011 Through 29-10-2011",
}