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Completed HORIZON European Commission

Making The Invisible Visible for Off-Highway Machinery by Conveying Extended Reality Technologies

€6.19M EUR

Funder European Commission
Recipient Organization Ttcontrol Gmbh
Country Austria
Start Date Jan 01, 2023
End Date Dec 31, 2025
Duration 1,095 days
Number of Grantees 11
Roles Participant; Third Party; Coordinator
Data Source European Commission
Grant ID 101092861
Grant Description

THEIA-XR (Making the invisible visible for off-highway machinery by conveying extended reality technologies) aims at improving human-machine interaction in mobile machinery by enhancing user technology fit and extending reality technologies and functionalities.

The results will make the invisible visible respectively the non-perceivable perceivable to the human operator, extending the perceivable range of the operator without negatively influencing the performance of the human while controlling the machinery.

The project will ensure positive impact of eXtended Reality technologies on the safety, security trustworthiness and societal aspects of the interaction between the machine, the human operator and public/non-users, and furthermore create an XR workplace that enables positive user experiences of self-efficacy and meaningfulness of work.THEIA-XR will leverage a human-centred transdisciplinary and scenario-based co-design methodology with users, stakeholders and multidisciplinary researchers as a fully integrated project team.

This methodology serves to collect human requirements and to design, develop and deploy the extended reality technologies for information presentation and interaction in the off-highway domain.

The targeted extended reality technologies will enhance conventional human-machine interfaces through multi-modal information and interaction technologies, deploying innovative data visualization methods, force feedback technology and acoustic information.The THEIA-XR approach for improving the human operator tasks by deploying extended reality technologies will be initially validated and tested in three uses cases in the off-highway domain, targeting snow grooming, logistics and construction scenarios, integrating real end-users, public/non-users and real-life data from dedicated industrial environments.

All Grantees

Prinoth Spa; Technische Universitaet Graz; Teknologian Tutkimuskeskus Vtt Oy; Universite Du Luxembourg; Kalmar Finland Oy; Tttech Computertechnik Ag; Hochschule Der Medien; Haption Sa; Ttcontrol Gmbh; Creanex Oy; Technische Universitaet Dresden

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