Extended Reality Application Framework for a Digital-Twin-Based Smart Crane

Autor: Chao Yang, Xinyi Tu, Juuso Autiosalo, Riku Ala-Laurinaho, Joel Mattila, Pauli Salminen, Kari Tammi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Applied Sciences, Vol 12, Iss 12, p 6030 (2022)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app12126030
Popis: Industry 4.0 is moving forward under technology upgrades, utilizing information technology to improve the intelligence of the industry, whereas Industry 5.0 is value-driven, aiming to focus on essential societal needs, values, and responsibility. The manufacturing industry is currently moving towards the integration of productivity enhancements and sustainable human employment. Such a transformation has deeply changed the human–machine interaction (HMI), among which digital twin (DT) and extended reality (XR) are two cutting-edge technologies. A manufacturing DT offers an opportunity to simulate, monitor, and optimize the machine. In the meantime, XR empowers HMI in the industrial field. This paper presents an XR application framework for DT-based services within a manufacturing context. This work aims to develop a technological framework to improve the efficiency of the XR application development and the usability of the XR-based HMI systems. We first introduce four layers of the framework, including the perception layer with the physical machine and its ROS-based simulation model, the machine communication layer, the network layer containing three kinds of communication middleware, and the Unity-based service layer creating XR-based digital applications. Subsequently, we conduct the responsiveness test for the framework and describe several XR industrial applications for a DT-based smart crane. Finally, we highlight the research challenges and potential issues that should be further addressed by analyzing the performance of the whole framework.
Databáze: Directory of Open Access Journals