Electric Vehicle Charging Socket Detection using YOLOv8s Model
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Abstract
This paper introduces the utilization of the latest small You Only Look Once version
8 – YOLOv8s convolutional neural network in an automatic electric vehicle charging
application study. The employment of a deep learning-based object detector is a novel and
significant aspect in robotic applications, since it is both, the initial and the fundamental step
in a series of robotic operations, where the intent is to detect and locate the charging socket
on the vehicle’s body surface. The aim was to use a renowned and reliable object detector to
ensure the reliable and smooth functioning of the deployed robotic vision system in an
industrial environment. The experiments demonstrated that the deployed YOLOv8s model
detects the charging socket successfully under various image capturing conditions, with a
detection rate of 97.23%.
- Title
- Electric Vehicle Charging Socket Detection using YOLOv8s Model
- Author
- Tadic, Vladimir
- Odry, Akos
- Vizvari, Zoltan
- Kiraly, Zoltan
- Felde, Imre
- Odry, Peter
- xmlui.dri2xhtml.METS-1.0.item-date-issued
- 2024
- xmlui.dri2xhtml.METS-1.0.item-rights-access
- Open access
- xmlui.dri2xhtml.METS-1.0.item-identifier-issn
- 1785-8860
- xmlui.dri2xhtml.METS-1.0.item-language
- en
- xmlui.dri2xhtml.METS-1.0.item-format-page
- 19 p.
- xmlui.dri2xhtml.METS-1.0.item-subject-oszkar
- yolov8s, electric vehicle charging socket, image processing, object detection, robotic applications, automotive applications
- xmlui.dri2xhtml.METS-1.0.item-description-version
- Kiadói változat
- xmlui.dri2xhtml.METS-1.0.item-identifiers
- DOI: 10.12700/APH.21.10.2024.10.8
- xmlui.dri2xhtml.METS-1.0.item-other-containerTitle
- Acta Polytechnica Hungarica
- xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalYear
- 2024
- xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalVolume
- 21. évf.
- xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalNumber
- 10. sz.
- xmlui.dri2xhtml.METS-1.0.item-type-type
- Tudományos cikk
- xmlui.dri2xhtml.METS-1.0.item-subject-area
- Műszaki tudományok - közlekedés- és járműtudományok
- xmlui.dri2xhtml.METS-1.0.item-publisher-university
- Óbudai Egyetem