Mobile Robot Vision-Based Navigation Using Self-Organizing and Incremental Neural Networks

被引：0

作者：

Tangruamsub, Sirinart ^{[1
]}

Tsuboyama, Manabu ^{[1
]}

Kawewong, Aram ^{[1
]}

Hasegawa, Osamu ^{[1
]}

机构：

[1] Tokyo Inst Technol, Imaging Sci & Engn Lab, Dept Computat Intelligence & Syst Sci, Midori Ku, Yokohama, Kanagawa 227, Japan

来源：

IJCNN: 2009 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1- 6 | 2009年

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：

A new approach for vision-based navigation in mobile robots is presented. Instead of incremental spectral clustering (ISC), which is considered state-of-the-art, the method of self-organizing incremental neural networks (SOINN) is used for visual space clustering. Using SOINN, the number of nodes in the topological map matches well with the environment. The time used for incremental map building is markedly less than that used for ISC. Furthermore, the rate of single image classification is higher than that of ISC.

引用

页码：1103 / 1110

页数：8

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