A New Classification Technique in Mobile Robot Navigation

Nurmaini, Siti and Tutuko, Bambang (2011) A New Classification Technique in Mobile Robot Navigation. TELKOMNIKA, 9 (3). pp. 453-464. ISSN 1693-6930

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Abstract

This paper presents a novel pattern recognition algorithm that use weightless neural network(WNNs) technique.This technique plays a role of situation classifier to judge the situation around the mobile robot environment and makes control decision in mobile robot navigation. The WNNs technique is choose due to significant advantages over conventional neural network, such as they can be easily implemented in hardware using standard RAM, faster in training phase and work with small resources. Using a simple classification algorithm, the similar data will be grouped with each other and it will be possible to attach similar data classes to specific local areas in the mobile robot environment. This strategy is demonstrated in simple mobile robot powered by low cost microcontrollers with 512 bytes of RAM and low cost sensors. Experimental result shows, when number of neuron increases the average environmental recognition rate has risen from 87.6% to 98.5%.The WNNs technique allows the mobile robot to recognize many and different environmental patterns and avoid obstacles in real time. Moreover, by using proposed WNNs technique mobile robot has successfully reached the goal in dynamic environment compare to fuzzy logic technique and logic function, capable of dealing with uncertainty in sensor reading, achieving good performance in performing control actions with 0.56% error rate in mobile robot speed.

Item Type: Article
Additional Information: Department of Computer Engineering , Faculty of Computer Science, Sriwijaya University Jl. Raya Palembang-Prabumulim Km. 32 Indralaya, Ogan Ilir 30662, Palembang, Indonesia
Uncontrolled Keywords: environmental classification, mobile robot, weightless neural network
Subjects: Q Science > Q Science (General) > Q1-295 General
Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science
T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 56401-Computer Engineering (D3)
Depositing User: Dr. Ir. MT Siti Nurmaini
Date Deposited: 30 Sep 2019 03:17
Last Modified: 30 Sep 2019 03:17
URI: http://repository.unsri.ac.id/id/eprint/8836

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