ARTIFICIAL NEURAL NETWORKS FOR ROBOTICS COORDINATE TRANSFORMATION

被引：7
|
作者：
AYLOR, S [1 ]
RABELO, L [1 ]
ALPTEKIN, S [1 ]
机构：
[1] OHIO UNIV,DEPT IND & SYST ENGN,ATHENS,OH 45701
来源：
COMPUTERS & INDUSTRIAL ENGINEERING | 1992年 / 22卷 / 04期
关键词：
D O I：
10.1016/0360-8352(92)90023-D
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Artificial neural networks with such characteristics as learning, graceful degradation, and speed inherent to parallel distributed architectures might provide a flexible and cost solution to the real time control of robotics systems. In this investigation artificial neural networks are presented for the coordinate transformation mapping of a two-axis robot modeled with Fischertechnik physical modeling components. The results indicate that artificial neural systems could be utilized for practical situations and that extended research in these neural structures could provide adaptive architectures for dynamic robotics control.
引用
收藏
页码：481 / 493
页数：13
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