Operationalizing learning designs
Structured worksheets are converted into deployable applications, preserving learning objectives, tasks, and scene requirements.
MASTER Open Call #2 · Horizon Europe
Immersive AI for industrial robotics training.
TI-RAX leverages multi-agent, generative artificial intelligence to develop extended-reality training environments where learners can practise industrial robotics in safe, realistic, and repeatable simulations.
Industrial training requires more than observation. Learners need to act, decide, fail safely, and repeat. TI-RAX transforms pedagogical designs into immersive simulations, closing the gap between instructional planning and deployable training.
Research objectives
From educational design to simulation.
TI-RAX addresses core barriers in the creation and adoption of extended-reality training for industrial contexts.
Simulating hazardous procedures
High-risk industrial situations are reproduced in controlled virtual environments, enabling safety training without physical exposure.
Scaling immersive content creation
A multi-agent generation pipeline supports the design, production, and integration of XR scenes for the VIROO platform.
Initial use cases
Concrete industrial scenarios. Scientific training design.
The first TI-RAX simulations focus on industrial procedures where immersive practice can improve operational safety and readiness.
Automotive battery sorting
Decision-making and procedural training in a robotics-enabled industrial workflow.
End-of-life refrigerator dismantling
Safe exploration of task sequencing, risk points, and process execution in a simulated environment.
Workflow
A reproducible path to immersive training.
1
Specify
Define educational objectives, learner actions, safety conditions, and scene elements.
2
Generate
Use teams of generative-based agents to assist scene design and implementation.
3
Integrate
Deploy the generated scene within the VIROO application ecosystem across systems.
4
Train
Enable learners to practise procedures through repeatable virtual experiences.
Open resources
Project assets and technical material.
Resources are openly available for inspection, reuse, contribution, and evaluation.
Educational worksheets
Structured designs defining objectives, tasks, interactions, and simulation requirements.
Multi-agent pipeline
Multi-agent generation framework supporting creation of immersive experiences.
Scene source files
Source code, Unity assets, and deployable immersive training application projects.
User manuals
Technical and operational documentation for deployment, configuration, and learner access.
End-user applications
Interactive industrial training simulations accessible directly through the VIROO platform.
Walkthrough videos
Recorded demonstrations showcasing immersive learner interactions.
Consortium
Scientific and industrial expertise.
TI-RAX brings academic expertise in artificial intelligence and education with industry experience in digital transformation.
University of Cagliari
Scientific partner in generative artificial intelligence, artificial intelligence in education, and deep learning technologies.
R2M Solution
Business development partner with industry experience in information and communication technologies.
Get involved
Contribute to safer, more accessible industrial training.
We welcome code contributions, technical feedback, user experience insights, and participation in evaluation activities.