Elimination of the collision states of the effectors of industrial robots by application of neural networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F15%3A00240609" target="_blank" >RIV/68407700:21220/15:00240609 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.4028/www.scientific.net/AMM.798.276" target="_blank" >http://dx.doi.org/10.4028/www.scientific.net/AMM.798.276</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.4028/www.scientific.net/AMM.798.276" target="_blank" >10.4028/www.scientific.net/AMM.798.276</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Elimination of the collision states of the effectors of industrial robots by application of neural networks

Popis výsledku v původním jazyce

The article deals with the usage of methods of learning algorithms of neural networks for solving of collision states problem within multi-robotic cooperation. Nowadays, multi-robotic cooperation is a highly used method of work of two or more industrial robots. The requirements for elimination of collision states are getting more difficult when the multi-robotic system is more complicated. Methods of neural networks provide suitable tools for solving of complex cooperating problems. In the beginning of the article, we discuss the term “collision state” and the possibilities of its solving. In the following chapter, we discuss the theory of neural networks and learning algorithms, which we applied in solving of the collision states. In the final chapter, we implemented the practical verification of the model neural network in JSNN programme. It consisted of creating and learning of the training data and subsequent verification of the test data.

Název v anglickém jazyce

Elimination of the collision states of the effectors of industrial robots by application of neural networks

Popis výsledku anglicky

The article deals with the usage of methods of learning algorithms of neural networks for solving of collision states problem within multi-robotic cooperation. Nowadays, multi-robotic cooperation is a highly used method of work of two or more industrial robots. The requirements for elimination of collision states are getting more difficult when the multi-robotic system is more complicated. Methods of neural networks provide suitable tools for solving of complex cooperating problems. In the beginning of the article, we discuss the term “collision state” and the possibilities of its solving. In the following chapter, we discuss the theory of neural networks and learning algorithms, which we applied in solving of the collision states. In the final chapter, we implemented the practical verification of the model neural network in JSNN programme. It consisted of creating and learning of the training data and subsequent verification of the test data.

Druh

D - Stať ve sborníku

CEP obor

JT - Pohon, motory a paliva

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Applied mechanics and materials

ISBN

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ISSN

1662-7482

e-ISSN

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Počet stran výsledku

6

Strana od-do

276-281

Název nakladatele

Trans Tech Publications Inc.

Místo vydání

Pfaffikon

Místo konání akce

Bratislava

Datum konání akce

16. 10. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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