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

Chao Yang*, Xinyi Tu, Juuso Autiosalo, Riku Ala-Laurinaho, Joel Mattila, Pauli Salminen, Kari Tammi

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)
91 Downloads (Pure)

Abstract

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.
Original languageEnglish
Article number6030
JournalApplied Sciences (Switzerland)
Volume12
Issue number12
DOIs
Publication statusPublished - 14 Jun 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • digital twin
  • extended reality
  • human-machine interaction
  • framework
  • crane

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