Ing./MSc. Internship Proposal in Computer Science : Edge-Assisted eXtended Reality Operated with Digital Twin for Aerospace Industry

Job description

Joining LINEACT at CESI for a research internship would be a fantastic opportunity to contribute to innovative projects while deepening my skills in a cutting-edge environment focused in Computer Science

Keywords

Cloud, Data compression, Edge, Extended Reality, Digital Twins, IIoT, Unity, OPCUA.

Abstract

Extended Reality (XR) and Digital Twin (DT) technologies are transforming the Industrial Internet of Things (IIoT), offering significant potential for next-generation industrial applications. This internship aims to enhance collaborative XR experiences coupled with DT to deliver improved Quality of Service (QoS) and Quality of Experience (QoE) for both on-site and remote users. Building on an existing XR environment that integrates DT and real-time pose estimation in Augmented Reality (AR), the project seeks to extend its application to the aerospace industry. Additionally, the internship will explore data compression techniques to enhance the realism and dynamism of XR interactions within the DT framework, thereby optimising the immersive experience.

Research Work

Scientific Fields :

Aerospace, Edge/Cloud Computing, Extended Reality, Digital Twin Technologies, and Human-Computer Interaction.

Work Program/Objectives:

The main aim of this Master’s thesis is to implement hybrid collaborative XR technologies for the aerospace industry.

The objectives/program include:

1. Conduct a comprehensive review of XR applications in aerospace and real-time collaboration in georeferenced environments to identify industry-specific use cases.

2. Design and implement collaborative XR scenarios for the aerospace sector, where on-site operators use AR while remote experts interact through VR. These scenarios will integrate the existing DT tools and real-world operational constraints to enhance system realism and improve the effectiveness of collaboration.

3. Optimize the XR offloading architecture for pose estimation and rendering by leveraging cloud infrastructure and containerized solutions to ensure modularity, scalability, and performance.

4. Incorporate OPC-UA for real-time data exchange with IIoT components and propose potential data compression techniques to reduce latency and bandwidth while maintaining performance quality.

5. Validate the solution in a real scenario involving multiple collaborative users co-located/remote locations using heterogeneous devices. Conduct experiments to assess the QoS/QoE for local and remote XR users.

Previous Work in the Laboratory

JENII project, is a remote learning initiative for the future industry, built upon immersive and collaborative environments centered around digital twins of real industrial systems.

Expected Scientific/Technical Output:

The expected outcomes include a comprehensive documentation report detailing the research, experiments, and evaluations conducted during the proof-of-concept phase, contributing to the academic knowledge base in XR and DT technologies. These contributions are anticipated to drive further innovation in the field and provide industrial partners with operational benefits, particularly through enhanced performance in real-world XR

applications, thereby supporting better decision-making, collaboration, and productivity in aerospace industries.

Context

Lab Presentation

CESI LINEACT (UR 7527), Laboratory for Digital Innovation for Businesses and Learning to Support the Competitiveness of Territories, anticipates and accompanies the technological mutations of sectors and services related to industry and construction. The historical proximity of CESI with companies is a determining element for our research activities. It has led us to focus our efforts on applied research close to companies and in partnership with them. A human-centered approach coupled with the use of technologies, as well as territorial networking and links with training, have enabled the construction of cross-cutting research; it puts humans, their needs and their uses, at the center of its issues and addresses the technological angle through these contributions.

Its research is organized according to two interdisciplinary scientific teams and several application areas:

• Team 1 "Learning and Innovating" mainly concerns Cognitive Sciences, Social Sciences and Management Sciences, Training Techniques and those of Innovation. The main scientific objectives are the understanding of the effects of the environment, and more particularly of situations instrumented by technical objects (platforms, prototyping workshops, immersive systems...) on learning, creativity and innovation processes.

• Team 2 "Engineering and Digital Tools" mainly concerns Digital Sciences and Engineering. The main scientific objectives focus on modeling, simulation, optimization and data analysis of cyber physical systems. Research work also focuses on decision support tools and on the study of human-system interactions in particular through digital twins coupled with virtual or augmented environments.

These two teams develop and cross their research in application areas such as:

• Industry 5.0,

• Construction 4.0 and Sustainable City,

• Digital Services.

Areas supported by research platforms, mainly that in Rouen dedicated to Factory 5.0 and those in Nanterre dedicated to Factory 5.0 and Construction 4.0.

Links to the research axes of the research team involved:

The project aims to leverage the synergies between the research areas of CPS modelling, design, and architecture, and the collaborative processes and digital tools within team 2 of CESI LINEACT.

Presentation of C2A project :

Supported by state investment as part of the France 2030 Plan, Campus Aero Adour (C2A) is a project to support the digital and environmental transition of the aeronautics industry in the Adour territory. As a laureate of the "AMI Compétences et Métiers d’Avenir" call for projects under the ’Producing Low-Carbon Aircraft’strand, C2A will benefit from State support through the France 2030 initiative over five years.

Desired profile

Required Skills

The candidate should possess a Master student or equivalent in Computer Science or Applied Mathematics.

She/He should have some knowledge and experience in a number of the following points:

• Scientific and Technical Skills:

– Solid programming and software development tools skills ( C#, Unity 3D, NodeJS, Docker and Python),

– Strong interest in XR technologies, digital twins, edge computing, and cloud architecture,

– knowledge in multiplayer programming in Unity would be appreciated

– Familiarity with networking concepts and protocols, particularly in the context of edge computing and cloud architecture,

– Effective communication skills in English/French and the ability to collaborate within a multidisciplinary team environment.

• Interpersonal Skills:

– Being autonomous, having initiative and curiosity,

– Ability to work in a team and have good interpersonal skills,

– Being rigorous.

Modalities:

File review and interview. All qualified individuals are encouraged to apply by sending to (hmkamdjou [at] cesi.fr, with the email subject: "[Application] Edge-Assisted XR with Digital Twin for Aerospace Industry". a cover letter, a resume, transcripts of M1 and the current year of M2 (or equivalent level), BSc/MSc/Ing.certificates and at least two recommendation letters. Applications will be processed as they arrive, early application is highly encouraged.

Application should include:

• Detailed Curriculum Vitae of the candidate. In case of a break in academic studies, please provide an explanation;

• A motivation letter explaining your motivations for pursuing a doctoral thesis;

• Transcripts of MASTER I and/or II and/or corresponding grade reports;

• BSc/MSc/Ing. certificates;

• Two recommendation letters.

Please submit all documents in a zip file titled FIRSTNAME_LASTNAME.zip.

Acknowledgements:

This work is conducted as part of Campus Aero Adour (C2A) project funded by the government under the France 2030 Plan.

References

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