X-Reality System Architecture for Industry 4.0 Processes

• Published in: Multimodal technologies and interaction Vol. 2; no. 4; p. 72
• Main Authors: Simões, Bruno, De Amicis, Raffaele, Barandiaran, Iñigo, Posada, Jorge
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2018
• Subjects: Application programming interface; applications of SAR; Augmented reality; Calibration; Cloud computing; Communication; Computer architecture; Configurations; Control equipment; Data retrieval; Digitization; Electronic devices; Flooring; Industrial applications; Industrial equipment; Industry 4.0; Infrastructure; Intelligence; Java; Manufacturing; Middleware; mixed reality; projected augmented reality; projector-camera systems; Prototypes; Scientific visualization; Sensors; Smartphones; Visualization; X-Reality
• DOI: 10.3390/mti2040072
• ISSN: 2414-4088

Information visualization has been widely adopted to represent and visualize data patterns as it offers users fast access to data facts and can highlight specific points beyond plain figures and words. As data comes from multiple sources, in all types of formats, and in unprecedented volumes, the need intensifies for more powerful and effective data visualization tools. In the manufacturing industry, immersive technology can enhance the way users artificially perceive and interact with data linked to the shop floor. However, showcases of prototypes of such technology have shown limited results. The low level of digitalization, the complexity of the required infrastructure, the lack of knowledge about Augmented Reality (AR), and the calibration processes that are required whenever the shop floor configuration changes hinders the adoption of the technology. In this paper, we investigate the design of middleware that can automate the configuration of X-Reality (XR) systems and create tangible in-site visualizations and interactions with industrial assets. The main contribution of this paper is a middleware architecture that enables communication and interaction across different technologies without manual configuration or calibration. This has the potential to turn shop floors into seamless interaction spaces that empower users with pervasive forms of data sharing, analysis and presentation that are not restricted to a specific hardware configuration. The novelty of our work is due to its autonomous approach for finding and communicating calibrations and data format transformations between devices, which does not require user intervention. Our prototype middleware has been validated with a test case in a controlled digital-physical scenario composed of a robot and industrial equipment.