Robot Control Using High Dimensional Neural Networks

被引：0

作者：

Maeda, Yutaka ^{[1
]}

Fujiwara, Takashi ^{[1
]}

Ito, Hidetaka ^{[1
]}

机构：

[1] Kansai Univ, Fac Engn, Osaka, Japan

来源：

2014 Proceedings of the SICE Annual Conference (SICE) | 2014年

关键词：

Robot Control; Complex-valued neural network; Quaternion neural network; Inverse kinematics;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we propose a position control scheme for actual robot system using high dimensional neural networks. Complex-valued neural network and quaternion neural network learn inverse kinematics of the robot systems. Control objectives are two dimensional SCARA robot and three dimensional robot. Tip of these robots are controlled by the high dimensional neural networks. Some results by an actual robot system are shown to confirm feasibility of these high dimensional neural networks as robot controllers.

引用

页码：738 / 743

页数：6