%0 Journal Article
%T Kinematic model identification and implementation of redundant robot based on neural networks<br>冗余度机器人运动模型的神经网络辨识及实现
%A JIANG Chun-fu
%A YU Yue-qing
%A LIU Ying-chun
%A <br>姜春福
%A 余跃庆
%A 刘迎春
%J 控制理论与应用
%D 2004
%I 
%X In order to increase the computational efficiency of neural networks,a new network model named state delay input dynamical recurrent neural network is presented in this study.This new neural network is also applied to the model identification of PowerCube\+\{TM\} modular robot system.The data of joint positions retrieved from the robot and the position of the end-effector measured by the OPTOTRAK 3020 are used as learning sets for neural network.The learning superiority of the new neural network is illustrated.
%K redundant robot
%K neural networks
%K identification<br>冗余机器人
%K 神经网络
%K 辨识
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=B535B6A36D19D92D&yid=D0E58B75BFD8E51C&vid=659D3B06EBF534A7&iid=38B194292C032A66&sid=F4BDB5452F9F5642&eid=73648F51F187AC5E&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=1&reference_num=6