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Detail publikačního výsledku
KACZMARCZYK, V.; BAŠTÁN, O.; HUSÁK, M.; BENEŠL, T.; BRADÁČ, Z.
Original Title
Robotic platform equipped with machine learning
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
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.
English abstract
Keywords
Industrial robotics, Industrial communication, Machine learning, Virtual commissioning, Fanuc, TensorFlow, Object detection
Key words in English
Authors
RIV year
2023
Released
20.05.2022
Publisher
Elsevier
Location
Sarajevo
Book
17th IFAC INTERNATIONAL CONFERENCE on PROGRAMMABLE DEVICES and EMBEDDED SYSTEMS - PDeS 2022
ISBN
2405-8963
Periodical
IFAC-PapersOnLine
Volume
55
Number
4
State
United Kingdom of Great Britain and Northern Ireland
Pages from
380
Pages to
386
Pages count
6
URL
https://www.sciencedirect.com/science/article/pii/S2405896322003780
Full text in the Digital Library
http://hdl.handle.net/
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" }