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Intelligent Low Cost Mobile Robot and Environmental Classification

by Siti Nurmaini
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 35 - Number 12
Year of Publication: 2011
Authors: Siti Nurmaini
10.5120/4545-6280

Siti Nurmaini . Intelligent Low Cost Mobile Robot and Environmental Classification. International Journal of Computer Applications. 35, 12 ( December 2011), 1-7. DOI=10.5120/4545-6280

@article{ 10.5120/4545-6280,
author = { Siti Nurmaini },
title = { Intelligent Low Cost Mobile Robot and Environmental Classification },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 35 },
number = { 12 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume35/number12/4545-6280/ },
doi = { 10.5120/4545-6280 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:21:46.526719+05:30
%A Siti Nurmaini
%T Intelligent Low Cost Mobile Robot and Environmental Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 35
%N 12
%P 1-7
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper low cost mobile robot is designed and developed. A tree diagram of material selection is used to help designer to determine the requirements of mobile robot process design. 5 pieces of low price infrared sensors and 8 bits low cost microcontroller-based system are utilized to process sensors signal and driving actuators to guide mobile robot movement. Fuzzy-Kohonen Network (FKN) method is embedded into the mobile robot as pattern recognition approach of 21 environmental classifications. We have fully implemented the system with a real mobile robot and made experiments for evaluating the mobile robot ability. As a result, we found out that the environment recognition is done well, that mobile robot successfully identified several environmental situations. Furthermore, our method is adaptive to noisy environments and produce satisfactory performance.

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Index Terms

Computer Science
Information Sciences

Keywords

Low cost mobile robot Pattern recognition Fuzzy-kohonen network Environmental recognition

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