Flexible Photorealistic VR Training System for Electrical Operators

Maik, Mikołaj; Sobociński, Paweł; Walczak, Krzysztof; Strugała, Dominik; Górski, Filip; Zawadzki, Przemysław

doi:10.1145/3564533.3564561

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…The scenario ontology and descriptors are comprehensively described in Section IV. The creation of synthetic 3D content for scenes, objects, and equipment is achievable through the use of our scene editor and the Unity game engine, but it is beyond the scope of this paper [19].…”

Section: Overview Of the Approachmentioning

confidence: 99%

Knowledge-Based Creation of Industrial VR Training Scenarios

Sobociński,

Flotyński,

Śliwicki

et al. 2023

Annals of Computer Science and Information Systems

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The application of virtual reality (VR) for building training systems has grown in popularity across diverse fields. This trend is particularly prevalent in Industry 4.0, where many real-world training scenarios can be expensive or pose potential dangers to trainees. The most important aspect of professional training is domain-specific knowledge, which can be expressed using the semantic web approach. This approach facilitates complex queries and reasoning against the representation of training scenarios, which can be useful for educational purposes. However, current methods and tools for creating VR training systems do not utilize semantic knowledge representation, making it difficult for domain experts without IT expertise to create, modify, and manage training scenarios. To address this issue, we propose an ontology-based representation and a method of modeling VR training scenarios. We demonstrate our approach by modeling VR training scenarios for Industry 4.0 in the field of the production of household equipment. The domain knowledge used represents training activities, potential errors, and equipment failures in a way comprehensible to domain experts.

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Section: Overview Of the Approachmentioning

confidence: 99%

Knowledge-Based Creation of Industrial VR Training Scenarios

Sobociński,

Flotyński,

Śliwicki

et al. 2023

Annals of Computer Science and Information Systems

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A Comprehensive Approach to the Analysis of VR Training Progress of Industry 4.0 Employees

Gałązkiewicz,

Maik,

Walczak

et al. 2023

Lecture Notes in Computer Science

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Knowledge-based approach to adaptive XR interface design for non-programmers

Maik,

Flotyński,

Walczak

2024

Vis Comput

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Customizing extended reality (XR) interfaces presents a significant challenge, especially for users with limited programming expertise. This paper introduces the method for adaptation of XR interfaces (MAXI-XR), a novel approach to simplify the customization process of XR user interfaces through knowledge technologies. MAXI-XR offers a user-friendly solution for interface design, supporting users with varying levels of technical skills. The basis of MAXI-XR is its Semantic Knowledge Base, which facilitates intelligent adaptations through advanced querying and reasoning, enabling the extraction of user-specific information for context-based XR interface adaptation. The functionality of MAXI-XR is demonstrated by its application in a VR stock market data visualization system. This system demonstrates MAXI-XR’s ability to adapt to complex and data-intensive environments according to user requirements, improving the interaction experience. Furthermore, the method’s scalability and ease of maintenance make it a versatile tool for a wide range of applications beyond stock market visualization, suggesting its potential for broader adoption in various XR domains.

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Flexible Photorealistic VR Training System for Electrical Operators

Cited by 3 publications

References 4 publications

Knowledge-Based Creation of Industrial VR Training Scenarios

Knowledge-Based Creation of Industrial VR Training Scenarios

A Comprehensive Approach to the Analysis of VR Training Progress of Industry 4.0 Employees

Knowledge-based approach to adaptive XR interface design for non-programmers

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