Development of object detection model for sizing safety measures in Human-Industrial mobile robot interaction

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dc.contributor.authorAslan, Tarik
dc.contributor.authorYagimli, Mustafa
dc.date.accessioned2024-06-13T20:18:27Z
dc.date.available2024-06-13T20:18:27Z
dc.date.issued2024
dc.departmentİstanbul Gedik Üniversitesien_US
dc.description.abstractIn human -robot interaction, single -level safety measures are traditionally applied, and employee -specific criteria are not taken into account. However, a new method can be developed using object detection technology, and the risk level of human -robot interaction can be determined by identifying employeespecific criteria such as the use of protective equipment and authorization levels, and different -sized safety measures can be applied depending on the risk magnitude. In this study, YOLOv5n, YOLOv8n, and SSD MobileNet V3 object detection models were developed and analyzed for this purpose. The results show that architectures belonging to the YOLO family run faster and achieve higher levels of accuracy. The YOLOv5n algorithm achieved a speed of 650 FPS with the use of a GPU and an F1 accuracy of 95.7% as a result of the evaluation with test data. The results show that object detection technology has reached an accuracy and speed that can be applied simultaneously with proximity senors, and that industrial mobile robots can detect worker characteristics and rate risks before taking safety measures. This allows for safer working environments, eliminates unnecessary precautions, and optimizes operational efficiency. In addition, this method can be applied in many sectors and areas to provide safe working environments.en_US
dc.identifier.doi10.17341/gazimmfd.1306981
dc.identifier.issn1300-1884
dc.identifier.issn1304-4915
dc.identifier.issue4en_US
dc.identifier.urihttps://doi.org/10.17341/gazimmfd.1306981
dc.identifier.urihttps://hdl.handle.net/11501/1369
dc.identifier.volume39en_US
dc.identifier.wosWOS:001236221100006en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherGazi Univ, Fac Engineering Architectureen_US
dc.relation.ispartofJournal of the Faculty of Engineering and Architecture of Gazi Universityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectObject Detectionen_US
dc.subjectRobot Safetyen_US
dc.subjectSafe Operationen_US
dc.subjectYolov5nen_US
dc.subjectSsd Mobilenet V3en_US
dc.titleDevelopment of object detection model for sizing safety measures in Human-Industrial mobile robot interactionen_US
dc.typeArticleen_US

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