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Управљање мобилним роботом за заобилажење препрека у 2D простору применом вештачких неуронских мрежа

Authors: Mitrović, S.; Jakovljević, Ž.; Dimić, Z.; Miljković, Z.;

Управљање мобилним роботом за заобилажење препрека у 2D простору применом вештачких неуронских мрежа

Abstract

U okviru ovog rada predstavljeni su inicijalni rezultati istraživanja u kreiranju sistema za upravljanje mobilnim robotom za kretanje u 2D prostoru sa preprekama. Sistem je zasnovan na upotrebi veštačkih neuronskih mreža i infracrvenih senzora rastojanja. Softversko rešenje je primenjeno na mikrokontroleru, sa ciljem da se upotrebom minimalne hardverske konfiguracije postigne adekvatan nivo mogućnosti snalaženja u prostoru. Opisane su korišćene veštačke neuronske mreže, dati su algoritmi upravljačkog i pomoćnog softvera i opisani su eksperimentalni rezultati. Projektovani sistem upravljanja uspešno je testiran na mobilnom robotu „Buggy“ u okviru eksperimentalnog okruženja postavljenog u Lola institutu.

In this paper, a neural networks based control system of a mobile robot for obstacle avoidance in 2D space is proposed. The system utilizes infrared distance sensors and neural networks for navigation around obstacles. Developed control software is implemented within microcontroller for achieving the adeqate level of space awareness while maintaing hardware configuration at a minimum. Developed neural networks will be described, along with control and auxiliary software and experimental results. Proposed control system has been successfully tested on a Mikroe Buggy mobile robot at Lola institute in Belgrade.

Country
Serbia
Keywords

mobilni robot, Mobilni robot, Mikrokontroler, veštačke neuronske mreže, Veštačke neuronske mreže, 2D prostor, Zaobilaženje prepreka, zaobilaženje prepreka, mikrokontroler

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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