The application of ART neural network to image processing for controlling a mobile vehicle

Author

Sugisaka, Masanori ; Dai, Fengzhi

Author_Institution

Dept. of Electr. & Electron. Eng., Oita Univ., Japan

Volume

3

fYear

2001

fDate

2001

Firstpage

1951

Abstract

This paper presents experimental results of pattern recognition for controlling a mobile vehicle by using adaptive resonance theory neural network (abbreviated to ART). The aim is to give a practical method to the pattern recognition by ART. ART, a kind of competitive neural network, can self-organize and self-stabilize in response to complex input vectors. New patterns are stored in such a fashion that existing ones are not forgotten or modified. Finally, experimental results and some future considerations are also given

Keywords

ART neural nets; control system synthesis; mobile robots; neurocontrollers; robot vision; self-organising feature maps; stability; vectors; ART neural network; adaptive resonance theory neural network; competitive neural network; complex input vectors; control design; control performance; image processing; mobile vehicle control; pattern recognition; self-organization; self-stabilization; Charge coupled devices; Charge-coupled image sensors; DC motors; Image processing; Neural networks; Pattern recognition; Process control; Stability; Subspace constraints; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on

Conference_Location

Pusan

Print_ISBN

0-7803-7090-2

Type

conf

DOI

10.1109/ISIE.2001.932011

Filename

932011