Evolutionary algorithms in robot calibration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F23%3A00373270" target="_blank" >RIV/68407700:21220/23:00373270 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1080/10426914.2023.2238368" target="_blank" >https://doi.org/10.1080/10426914.2023.2238368</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/10426914.2023.2238368" target="_blank" >10.1080/10426914.2023.2238368</a>
Alternative languages
Result language
angličtina
Original language name
Evolutionary algorithms in robot calibration
Original language description
Robots are universal mechanical systems that are now ubiquitous in manufacturing. One of the most important properties of industrial robots is their kinematic accuracy. Robot's accuracy is influenced by many factors including manufacture accuracy of mechanical parts and other aspects. Calibration is a technique that allows to identify design and other parameters of the robot to achieve its highest accuracy. There are widely used traditional kinematic calibration methods based on kinematic models of the robot. Simulation is used to compare results of traditional calibration method and a newly developed method based on multi-objective deep learning evolutionary algorithm. EvoDN2 was used together with a reference vector-based evolutionary algorithm, cRVEA, used for optimization, in order to find optimal estimates of the robot parameters. It is well known that the evalutionary algorithms are capable of dealing with noisy data from measurement. Results and comparison of both techniques are discussed and evaluated.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20302 - Applied mechanics
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Materials and Manufacturing Processes
ISSN
1042-6914
e-ISSN
1532-2475
Volume of the periodical
38
Issue of the periodical within the volume
16
Country of publishing house
GB - UNITED KINGDOM
Number of pages
20
Pages from-to
2051-2070
UT code for WoS article
001048238000001
EID of the result in the Scopus database
2-s2.0-85166940363