ML-based Digital Twin for anomaly detection: a case-study on Turtle soccer robots

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Samenvatting

In recent years, machine learning (ML) based digital twins (DTs) have seen widespread application in the anomaly detection domain. A search-based literature survey revealed that the majority of the case studies focus on large-scale systems (i.e., nuclear power plant, aerospace, and power grid) producing extensive data. Our work aims to investigate the performance of this technology in smaller-scale systems that generate less data. In this case study, we developed a ML-based DT of the mobility system, the omni wheels, of the Turtle soccer robots. The DT is capable of analyzing historical data collected from the physical robots and differentiating between damaged and undamaged wheels. Our experiments suggest that ML-based DT of small-scale systems is indeed capable of achieving relatively accurate results for anomaly detection use-cases.
Originele taal-2Engels
Titel2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's179-182
Aantal pagina's4
ISBN van elektronische versie979-8-3503-4235-2
DOI's
StatusGepubliceerd - 1 jan. 2024
Evenement2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) - Durres, Albanië
Duur: 6 sep. 20238 sep. 2023

Congres

Congres2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
Land/RegioAlbanië
StadDurres
Periode6/09/238/09/23

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