MIMESIS Joint Research Lab (2023 - 2028)

Advancing Human-Centric Systems Engineering

Exploring the potential of the Industrial Metaverse for Systems Engineering

Join the Community

The Motivations

Overcoming the Barriers to MBSE Adoption

Model-Based Systems Engineering (MBSE) is essential for managing complexity, yet its widespread adoption is hindered by several critical barriers:

  • The User Blind Spot in MBSE Tool Design: Rigid standards often overshadow usability, alienating non-specialist audiences.
  • Software bias: Software engineers frequently design systems to look like software, ignoring the spatial realities of physical products.
  • Communication breakdowns: Esoteric graphical representations and poor diagrammatic visual notations act as massive barriers to cross-disciplinary communication.
  • Cognitive overload: Users struggle with perceptual and conceptual integration processes when trying to make sense of highly codified models, but also information about the system is spread across multiple diagrams, requiring the architect and stakeholders to navigate these different diagrams to find relevant information dispersed among various displays and integrate it into a cohesive representation.
  • Siloed engineering: There is a struggle bridging the gap between the world of systems and other specific domain disciplines, specifically the persistent separation between MBSE and 3D CAD environments, leading to a severe lack of convergence.
  • Architectural disconnect: Difficulties persist in efficiently co-architecting the product architecture and its enabling systems simultaneously, creating a major barrier to true industrial product-process co-design.

Our Approach

Where MBSE Meets HCI

MIMESIS'Lab addresses these fundamental barriers by shifting toward a human-centered approach in the Industrial Metaverse. To overcome the limitations of traditional diagrammatic representations, our research focuses on the intersection of Model-Based Systems Engineering (MBSE) and Human-Computer Interaction (HCI), emphasizing the importance of visually rich and interactive 3D UIs. Human cognition is fundamentally spatial. While traditional MBSE tools force engineers to mentally decode abstract 2D nodes, edges, and nested tables, our approach leverages immersive 3D environments to map complex system architectures into tangible, navigable spaces.

This capitalizes on natural human spatial memory, proprioception, and peripheral awareness. By transforming abstract topological data into visually rich, interactive 3D metaphors, we naturally align with human cognitive capabilities. This drastically lowers the cognitive load, accelerates the comprehension of multi-layered industrial systems, and makes complex engineering data intuitively accessible to all stakeholders.

We invent collaborative, highly interactive systems modeling interfaces by mixing three fundamental interaction paradigms:

Computer-as-Tool (HCI)

To extend engineers' capabilities. We translate abstract 2D SysML/UML diagrams into 3D iconic and symbolic visual metaphors with high semantic transparency, lowering the cognitive load and directly supporting metacognitive processes.

Computer-as-Partner (AI)

To delegate complex analytical tasks to artificial agents. We integrate Generative AI and multi-level digital thread analytics to assist users in navigating complex system architectures, verifying constraints, and retrieving engineering knowledge.

Computer-as-Medium (CSCW)

To communicate with teammates. We design asymmetric collaboration environments that connect multidisciplinary teams (e.g., Systems Architects in VR, Maintenance Engineers on Desktop/AR) to foster shared metacognitive representations of the system.

Our Focus

Core Research Axes

Digital Threads
Research Axis 1

Review Model-Based System Architecture

Focusing on 3D User Interfaces for managing complex Digital Threads. We are exploring multimodal UI techniques that allow engineers to trace and maintain MBSE data across multiple views and levels of abstraction.

  • CAD-MBSE seamless data integration
  • 3D visual representations of SysML/UML
  • Analyzing digital threads with Generative AI assistance
Product Process
Research Axis 2

Design of Model-Based System Architecture

Co-architecting complex industrial product-process systems. Transitioning from abstract 2D diagrammatic representations to immersive 3D space allocations, interface routing, and factory layout flow analysis.

  • From CONOPS to Physical Decomposition in VR
  • Build principles and Factory Layout Editing
  • Quantitative and qualitative usability testing of 3D vs 2D UI
Collaboration
Research Axis 3

Asymmetric Collaboration for Architecting Systems

Enabling distinct engineering disciplines to work together seamlessly using different devices tailored to their specific needs. Ensuring mutual responsiveness and cognitive synchronization across the Virtuality-Reality continuum.

  • Mixed hardware collaboration (VR Headsets, Desktop, CAVE)
  • Connecting Systems Architects, Project Managers, and Domain Engineers
  • Shared metacognitive representations of complex data

See it in Action

Video & Photo Gallery

Demonstrations

Lab Snapshots

Digital Threads Analytics
Product Process Architecture
Multi-user VR Collaboration
Asymmetric Collaboration Interface

* Photos represent illustrative setups of industrial metaverse technologies from MIMESIS'Lab.

Academic Impact

Recent Publications

Recent Publication (2026). MIMESIS'Lab Research Team. 10.1109/IEEECONF67861.2026.11440866

Recent Publication (2025). MIMESIS'Lab Research Team. 10.1007/s10055-025-01302-1

Recent Publication (2024). MIMESIS'Lab Research Team. 10.1016/j.procir.2024.08.230

Recent Publication. MIMESIS'Lab Research Team. 10.1201/9781003666431-19

Exploring model-based systems architecting digital threads in virtual reality. S. C. Medina Galvis, R. Pinquié, B. Paterne (2024). IFIP 21st International Conference on Product Lifecycle Management (PLM), Bangkok, Thailand. Link

Exploring the potential of virtual reality for model-based systems architecting. H. Wang (2024). Doctoral dissertation, Université Grenoble Alpes. Link

Human-centric co-design of model-based system architecture. R. Pinquié, H. Wang, F. Noël (2023). 33rd CIRP Design Conference, Sydney. Procedia CIRP. Vol. 109, pp. 472-477. Link

Un environnement virtuel immersif, interactif et collaboratif pour les revues de conception basées sur les modèles. V. Romero (2022). Doctoral dissertation, Université Grenoble Alpes. Link

A user-centric computer-aided verification process in a virtuality-reality continuum. V. Romero, R. Pinquié, F. Noël. (2022). Computers in Industry, Vol. 140. Link

An open benchmark exercise for model-based design reviews. V. Romero, R. Pinquié, F Noël. (2022). PLM 2022. IFIP Advances in Information and Communication Technology, vol 667. Springer. Link

Who We Are

Research Team & Committees

Research Team

  • Romain Pinquié
    Scientific Coordinator & Associate Prof. (Univ Grenoble Alpes, CNRS, Grenoble INP, G-SCOP)
    romain.pinquie@grenoble-inp.fr
  • Frédéric Noel
    Full Professor (G-SCOP UMR 5272)
  • Gilles Foucault
    Associate Professor (G-SCOP UMR 5272)
  • Camilo Medina & Ghislain Mugisha
    PhD Candidates (G-SCOP UMR 5272)
  • Haobo Wang
    Post-doctoral research fellow (G-SCOP UMR 5272)
  • Baptiste Paterne & Joshuel Kuilwijk
    XR Software Engineers (G-SCOP UMR 5272)

Committees

Executive Committee
  • Romain Pinquié & Frédéric Noel (G-SCOP UMR 5272)
  • Hugo Falgarone (CEO SkyReal) & Benjamin Ray (CTO SkyReal)
Steering Committee
  • Executive committee members
  • Peggy Zwolinski (Head of G-SCOP UMR CNRS)
  • Valérie Perrier (VP Scientific Board Univ Grenoble Alpes)
  • Ahmed Lbath (Head of Carnot LSI)
Scientific and Industrial Committee
  • Executive committee members
  • Nicolas Chevassus (Head of Ariane 6 Digital Transformation, Ariane Group)
  • Frédéric Mérienne (Full Prof., XR expert, Arts et Métiers ParisTech)
  • Françoise Darses (Full Prof., Cognitive ergonomics expert, Institute for Biomedical Research of Defense)