Optical positioning realized on raspberry Pi computer board

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F19%3A00537481" target="_blank" >RIV/60162694:G43__/19:00537481 - isvavai.cz</a>

Výsledek na webu

<a href="https://transportmeans.ktu.edu/wp-content/uploads/sites/307/2018/02/Transport-means-2019-Part-2.pdf" target="_blank" >https://transportmeans.ktu.edu/wp-content/uploads/sites/307/2018/02/Transport-means-2019-Part-2.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Optical positioning realized on raspberry Pi computer board

Popis výsledku v původním jazyce

This paper deals with optical positioning using artificial neural network for position. The method is based on changes in geometric pattern created by point light sources in the captured picture due to changes in camera position relative to those sources. The geometric pattern is created by the LED-based light sources placed in specific positions on the optical beacon. The LED positions are captured by daylight camera and the mutual position of the LEDs in the captured picture serves as the input data for the artificial neural network (ANN). Based on the input data the ANN determines the relative position of the optical beacon and the camera - the distance and positional angles. The method is realized on Raspberry Pi computer board. The description of mentioned method realization on Raspberry Pi and the results from experimental measurements are presented.

Název v anglickém jazyce

Optical positioning realized on raspberry Pi computer board

Popis výsledku anglicky

This paper deals with optical positioning using artificial neural network for position. The method is based on changes in geometric pattern created by point light sources in the captured picture due to changes in camera position relative to those sources. The geometric pattern is created by the LED-based light sources placed in specific positions on the optical beacon. The LED positions are captured by daylight camera and the mutual position of the LEDs in the captured picture serves as the input data for the artificial neural network (ANN). Based on the input data the ANN determines the relative position of the optical beacon and the camera - the distance and positional angles. The method is realized on Raspberry Pi computer board. The description of mentioned method realization on Raspberry Pi and the results from experimental measurements are presented.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Transport Means - Proceedings of the International Conference

ISBN

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ISSN

1822-296X

e-ISSN

2351-7034

Počet stran výsledku

5

Strana od-do

533-537

Název nakladatele

Kaunas University of Technology

Místo vydání

Kaunas, Lithuania

Místo konání akce

Palanga,Lithuania

Datum konání akce

2. 10. 2019

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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