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Pregled bibliografske jedinice broj: 1169115

Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms


Baressi Šegota, Sandi; Anđelić, Nikola; Car, Zlatan; Šercer, Mario
Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms // Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 29 (2022), 1; 101-107 doi:10.17559/TV-20210204092154 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1169115 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms

Autori
Baressi Šegota, Sandi ; Anđelić, Nikola ; Car, Zlatan ; Šercer, Mario

Izvornik
Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku (1330-3651) 29 (2022), 1; 101-107

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
artificial intelligence ; multilayer perceptron ; regression ; robot grasp robustness ; shadow smart grasping system

Sažetak
Predicting the quality of the robot end-effector grasp quality during an industrial robot manipulator operation can be an extremely complex task. As is often the case with such complex tasks, Artificial Intelligence methods may be applied to attempt the creation of a model - if sufficient data exists. The presented dataset uses a publicly available dataset, consisting of 992632 measurements of position, torque, and velocity - for each of the three joints of three fingers of the simulated end-effector. The dataset is first analyzed and pre- processed to prepare it for model training. The duplicate values are removed from the dataset, as well as the statistical outliers. Then, a multilayer perceptron (MLP) machine learning algorithm is applied to 80% of the data contained in the dataset, using the Grid Search algorithm to determine the best combination of MLP hyperparameters. As the dataset consists of torque, velocity, and speed measurements for separate joints and fingers of the tested end-effector the testing is performed to see if a subset of the inputs may be used to regress the robustness of the given grip. The normalization of the dataset is also applied, and its effect on the regression quality is tested. The results, evaluated with the coefficient of determination, show that while the best model is achieved using all the possible inputs, a satisfactory result can be obtained using only velocity and torque. The results also show that the normalization of the dataset improves the regression quality in all the observed cases.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Strojarstvo, Temeljne tehničke znanosti



POVEZANOST RADA


Projekti:
InoUstZnVO-CIII-HR-0108-10 - Concurrent Product and Technology Development - Teaching, Research and Implementation of Joint Programs Oriented in Production and Industrial Engineering (Car, Zlatan, InoUstZnVO - CEEPUS) ( POIROT)
EK-EFRR-KK.01.2.2.03.0004 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan; Slavić, Nataša; Vilke, Siniša, EK - KK.01.2.2.03) ( POIROT)
EK-EFRR-KK.01.1.1.02.0023 - Razvojno-edukacijski centar za metalsku industriju – Metalska jezgra Čakovec (Car, Zlatan, EK - KK.01.1.1.02) ( POIROT)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-275-1447 - Razvoj inteligentnog ekspertnog sustava za online diagnostiku raka mokračnog mjehura (Car, Zlatan, NadSve - UNIRI potpore) ( POIROT)
EK-KF-KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Lončarić, Sven; Petrović, Ivan; Šmuc, Tomislav; Jokić, Andrej, EK - KK.01.1.1.01) ( POIROT)

Profili:

Avatar Url Zlatan Car (autor)

Avatar Url Zlatan Car (autor)

Avatar Url Mario Šercer (autor)

Avatar Url Sandi Baressi Šegota (autor)

Avatar Url Nikola Anđelić (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada doi hrcak.srce.hr

Citiraj ovu publikaciju:

Baressi Šegota, Sandi; Anđelić, Nikola; Car, Zlatan; Šercer, Mario
Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms // Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 29 (2022), 1; 101-107 doi:10.17559/TV-20210204092154 (međunarodna recenzija, članak, znanstveni)
Baressi Šegota, S., Anđelić, N., Car, Z. & Šercer, M. (2022) Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms. Tehnički vjesnik : znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku, 29 (1), 101-107 doi:10.17559/TV-20210204092154.
@article{article, author = {Baressi \v{S}egota, Sandi and An\djeli\'{c}, Nikola and Car, Zlatan and \v{S}ercer, Mario}, year = {2022}, pages = {101-107}, DOI = {10.17559/TV-20210204092154}, keywords = {artificial intelligence, multilayer perceptron, regression, robot grasp robustness, shadow smart grasping system}, journal = {Tehni\v{c}ki vjesnik : znanstveno-stru\v{c}ni \v{c}asopis tehni\v{c}kih fakulteta Sveu\v{c}ili\v{s}ta u Osijeku}, doi = {10.17559/TV-20210204092154}, volume = {29}, number = {1}, issn = {1330-3651}, title = {Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms}, keyword = {artificial intelligence, multilayer perceptron, regression, robot grasp robustness, shadow smart grasping system} }
@article{article, author = {Baressi \v{S}egota, Sandi and An\djeli\'{c}, Nikola and Car, Zlatan and \v{S}ercer, Mario}, year = {2022}, pages = {101-107}, DOI = {10.17559/TV-20210204092154}, keywords = {artificial intelligence, multilayer perceptron, regression, robot grasp robustness, shadow smart grasping system}, journal = {Tehni\v{c}ki vjesnik : znanstveno-stru\v{c}ni \v{c}asopis tehni\v{c}kih fakulteta Sveu\v{c}ili\v{s}ta u Osijeku}, doi = {10.17559/TV-20210204092154}, volume = {29}, number = {1}, issn = {1330-3651}, title = {Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms}, keyword = {artificial intelligence, multilayer perceptron, regression, robot grasp robustness, shadow smart grasping system} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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