Template concept for VR environments: A case study in VR-based safety training for human–robot collaboration

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Morteza Dianatfar , Eeva Järvenpää , Niko Siltala , Minna Lanz
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引用次数: 0

Abstract

The industry 4.0 vision has accelerated technology development, particularly in the use of augmented reality (AR) and virtual reality (VR) in industry, such as the metaverse. However, creating VR environments is known to be a laborious task, which means their full potential is not yet fully utilized. There is a need for a reusable VR model that enables faster generation and population of VR environments. This research aims to find solutions for quicker development and deployment of VR environments in an industrial context. Specifically, this paper proposes one solution for creating and modifying these environments more efficiently. The focus of the research, along with the associated industrial use cases, is to develop safety training for human–robot collaboration in final assembly scenarios using VR environments. The paper will introduce a template concept, which includes individual templates and the full architecture to deploy these templates, allowing for faster modification of VR environments to meet specific use case needs. This template concept is developed using two separate use cases from academia and industry.
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
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