Adaptation, learning, and evolutionary computing for intelligent robots

被引：0
|
作者：
Fukuda, T
Shimojima, K
机构：
[1] Nagoya Univ, Dept Micro Syst Engn, Chikusa Ku, Nagoya, Aichi 46401, Japan
[2] MITI, AIST, Natl Res Inst Nagoya, Dept Mat Proc,Kita Ku, Nagoya, Aichi 462, Japan
来源：
COMPUTATIONAL INTELLIGENCE: THEORY AND APPLICATIONS | 1997年 / 1226卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
There have been growing demands for the intelligent systems for many areas. In this lecture, the methodologies for the adaptation, learning and evolutionary computing will be shown to make robotic system more intelligent through Fuzzy, Neuro and Genetic Algorithm basisses. Robotic manipulators can generate the optimal trajectory automatically. Mobile robots can find the path and work cooperatively, by sensing the environments, scheduling the optional path and actuating properly. Some of the examples are also shown in this presentation.
引用
收藏
页码：217 / 228
页数：12
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