Baza Publikacji Pracowników Politechniki Lubelskiej

Status:
Autorzy:	Kluz Rafał, Antosz Katarzyna, Trzepiecinski Tomasz, Gola Arkadiusz
Dyscypliny:
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Wersja dokumentu:	Drukowana \| Elektroniczna
Język:	angielski
Strony:	41 - 48
Scopus® Cytowania:	2
Bazy:	Scopus
Efekt badań statutowych	NIE
Materiał konferencyjny:	NIE
Publikacja OA:	NIE
Abstrakty:	angielski
	Industrial robots are an integral part of modern manufacturing systems. In order to fully use their potential, the information related to the robot’s accuracy should be known first of all. In most cases, the information considering robot’s errors, provided in a technical specification, is scarce. That’s why, this paper presents the issues of determining the error of industrial robots positioning repeatability. A neural mathematical model that allows for predicting its value with the error less than 5% was designed. The obtained results were compared to a classical mathematical model. It was revealed that a well-trained neural network enables the prediction of the error of positioning repeatability with the doubled accuracy.

Predicting the error of a Robot’s positioning repeatability with artificial neural networks