Methods and Technologies of Automated Learning for Improvement of Autonomous Robots Adaptivity

被引：0

作者：

Man'ko, S., V ^{[1
]}

Lokhin, V. M. ^{[1
]}

Romanov, M. P. ^{[1
]}

Romanov, A. M. ^{[1
]}

Stashkevich, M. A. ^{[1
]}

Panin, A. S. ^{[1
]}

机构：

[1] Moscow State Univ Informat Technol Radio Engn & E, MIREA, Moscow, Russia

来源：

PROCEEDINGS OF THE 2016 IEEE NORTH WEST RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (ELCONRUSNW) | 2016年

关键词：

self-learning; neural networks; robotics; evolutionary classification forest; autonomous robots;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper discusses a problem of automated learning based on analysis of a sensor array data, accumulated during the autonomous robot life-cycle, and a generalized experience of the robot operation results in different situations. The solution based on complex application of classification tree methods, evolution and neural-network algorithms is introduced.

引用

页码：277 / 282

页数：6