Suitable ASP U-Net training algorithms for grasping point detection of nontrivial objects

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F22%3A39919564" target="_blank" >RIV/00216275:25530/22:39919564 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CODIT55151.2022.9803900" target="_blank" >http://dx.doi.org/10.1109/CODIT55151.2022.9803900</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CODIT55151.2022.9803900" target="_blank" >10.1109/CODIT55151.2022.9803900</a>

Result language
angličtina
Original language name
Suitable ASP U-Net training algorithms for grasping point detection of nontrivial objects
Original language description
Robotic manipulation with nontrivial or irregular objects, which provide various types of grasping points, is of both academic and industrial interest. Recently, a powerful data-driven ASP U-Net deep neural network has been proposed to detect feasible grasping points of manipulated objects using RGB data. The ASP U-Net showed the ability to detect feasible grasping points with exceptional accuracy and more than acceptable inference times. So far, the network has been trained using an Adam optimizer only. However, in order to optimally utilize the potential of ASP U-Net, it was necessary to perform a systematic investigation of suitable training algorithms. Therefore, the aim of this contribution was to extend the impact of ASP U-Net by recommending suitable training algorithms and their parameters based on the result of training experiments.
Czech name
—
Czech description
—

Project
<a href="/en/project/EF17_049%2F0008394" target="_blank" >EF17_049/0008394: Cooperation in Applied Research between the University of Pardubice and companies, in the Field of Positioning, Detection and Simulation Technology for Transport Systems (PosiTrans)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2022 8th International Conference on Control, Decision and Information Technologies (CoDIT) : proceedings
ISBN
978-1-66549-608-7
ISSN
2576-3547
e-ISSN
2576-3555
Number of pages
6
Pages from-to
1586-1591
Publisher name
IEEE (Institute of Electrical and Electronics Engineers)
Place of publication
New York
Event location
Istanbul
Event date
May 17, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000846862800272

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