Imagine a digital assistant in a headset that knows exactly when to speak and how to gesture so it doesn't feel awkward or intrusive. Instead of a clunky interface, it acts more like a polite human who understands the room and your mood. This work creates a guidebook and a set of tools to make these digital experiences feel natural and trustworthy.
Current XR systems are often rejected by users because they feel unnatural, intrusive, or untrustworthy. This creates a barrier to mass adoption and increases the time and cost for companies to bring XR products to market.
A SERMAS Toolkit and Methodology for designing socially-acceptable XR, and a prototypical XR Agent capable of natural language and gesture-based communication.
If you are a luxury store dealing with customers who find VR headsets intimidating — this project developed a Toolkit that ensures digital assistants use natural gestures and social cues to make the shopping experience feel welcoming.
If you are a training center dealing with students who struggle to learn from rigid VR simulations — this project developed an XR Agent that adapts to the user's mental state and provides relevant information in a human-like way.
If you are a clinic dealing with patients who distrust automated XR therapy — this project developed a methodology to make systems transparent and secure, increasing user trust and acceptance.
Based on available project data, specific pricing or cost structures for the Toolkit are not provided.
The project aims to enhance the competitiveness of vendors by cutting down time-to-market and applying the Toolkit to industrial case studies from real-world scenarios.
Based on available project data, the specific licensing terms for the SERMAS Methodology and Toolkit are not detailed.
Yes, the project specifically defines functional and non-functional requirements including security and privacy to ensure the systems are safe and trusted.
The SERMAS XR Agent is designed as a general-purpose system combining hardware, software, and algorithmic modules to allow frictionless interaction.
The consortium is well-balanced for technology transfer, featuring a 38% industry ratio with 3 industrial partners and 1 SME. With 8 partners across 5 countries (IT, CH, DE, IE, UK), the project blends academic research from 4 universities with practical industrial application, ensuring the resulting Toolkit is grounded in real-world business needs.
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