Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikačního výsledku
KACZMARCZYK, V.; BAŠTÁN, O.; HUSÁK, M.; BENEŠL, T.; BRADÁČ, Z.
Originální název
Robotic platform equipped with machine learning
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
Automatic lines equipped with stationary robots are a key element of the industry. The robots are integrated into production lines, to meet basic, repetitive operations, with a finite degree of variability in internal programs. Reprogramming in terms of, for example, changing a manufactured, manipulated part is time-consuming and cost-effective. However, the development of today's machine learning algorithms is only carefully integrated in this market segment. Manufacturers do not provide their closed systems with a sufficient degree of programming variability. The solution tries to outline this work, which complements the standard industrial robot with a cognitive interface. Such a robot is able to learn new programs and make production changes on the fly.
Anglický abstrakt
Klíčová slova
Industrial robotics, Industrial communication, Machine learning, Virtual commissioning, Fanuc, TensorFlow, Object detection
Klíčová slova v angličtině
Autoři
Rok RIV
2023
Vydáno
20.05.2022
Nakladatel
Elsevier
Místo
Sarajevo
Kniha
17th IFAC INTERNATIONAL CONFERENCE on PROGRAMMABLE DEVICES and EMBEDDED SYSTEMS - PDeS 2022
ISSN
2405-8963
Periodikum
IFAC-PapersOnLine
Svazek
55
Číslo
4
Stát
Spojené království Velké Británie a Severního Irska
Strany od
380
Strany do
386
Strany počet
6
URL
https://www.sciencedirect.com/science/article/pii/S2405896322003780
BibTex
@inproceedings{BUT177979, author="Václav {Kaczmarczyk} and Ondřej {Baštán} and Michal {Husák} and Tomáš {Benešl} and Zdeněk {Bradáč}", title="Robotic platform equipped with machine learning", booktitle="17th IFAC INTERNATIONAL CONFERENCE on PROGRAMMABLE DEVICES and EMBEDDED SYSTEMS - PDeS 2022", year="2022", journal="IFAC-PapersOnLine", volume="55", number="4", pages="380--386", publisher="Elsevier", address="Sarajevo", doi="10.1016/j.ifacol.2022.06.063", issn="2405-8971", url="https://www.sciencedirect.com/science/article/pii/S2405896322003780" }