In mixed reality (MR) telepresence applications, the differences between participants' physical environments can interfere with effective collaboration. For asymmetric tasks, users might need to access different resources (information, objects, tools) distributed throughout their room. Existing intersection methods do not support such interactions, because a large portion of the telepresence participants' rooms become inaccessible, along with the relevant task resources. We propose MRUnion, a Mixed Reality Telepresence pipeline for asymmetric task-aware 3D mutual scene generation. The key concept of our approach is to enable a user in an asymmetric telecollaboration scenario to access the entire room, while still being able to communicate with remote users in a shared space. For this purpose, we introduce a novel mutual room layout called Union. We evaluated 882 space combinations quantitatively involving two, three, and four combined remote spaces and compared it to a conventional Intersect room layout. The results show that our method outperforms existing intersection methods and enables a significant increase in space and accessibility to resources within the shared space. In an exploratory user study (N=24), we investigated the applicability of the synthetic mutual scene in both MR and VR setups, where users collaborated on an asymmetric remote assembly task. The study results showed that our method achieved comparable results to the intersect method but requires further investigation in terms of social presence, safety and support of collaboration. From this study, we derived design implications for synthetic mutual spaces.

The concept of data-centered companies is of rapidly increasing interest within the process industry due to applications like data analysis, plant optimization and visualization. However, chemical companies face high barriers regarding the wide variety and heterogeneity of data along the brownfield plant lifecycle caused by the long history of tool-focused enterprises. This paper proposes an Information Model architecture for the process industry and an approach to overcome the hurdles associated with brownfield plants and information mapping.

Creating digital representations of industrial facilities presents substantial opportunities for the industry. The development of digital twins opens up many prospective applications for industrial plants, such as facilitating virtual training environments, streamlining change management, and providing real-time understanding of remote scenes. However, creating and maintaining these digital twins involves complex tasks, including scanning industrial plants and annotating their subsystems. Many use cases necessitate specifying a Volume of Interest (VoI) for further processing while presenting severe environmental challenges for segmentation quality and worker safety. Besides that, widespread adoption also depends on creating methods that are easy to use, even for workers with limited 3D interaction knowledge. Currently, no commonly implemented method fulfills all these diverse requirements. This paper introduces an approach for specifying a VoI in industrial scenarios. Our approach defines a volume by intersecting the projection of hand-drawn surroundings on a small number of pictures of the target volume, utilizing Augmented Reality and Voxel Carving. It can successfully handle various sizes of target volumes and delivers an appropriately detailed result. Applying qualitative discussions and a quantitative evaluation, we ensure our application meets all requirements posed by the scenarios. This simple interaction metaphor, tailored to specific use cases, can serve as a versatile pattern for various digital twin scenarios. It offers a valuable alternative to 3D primitive-based segmentation methods.