When it comes to snow groomers, excavators or crane vehicles, how can their operation be optimized even in difficult conditions and made safer for people in and around the vehicle? An international research team, including the Institute of Visual Computing at Graz University of Technology (TU Graz), investigated this question as part of the THEIA-XR project.

The researchers aimed to improve human-machine interaction through the use of extended reality technologies. The focus was on the operator, whose field of perception was to be expanded without negatively affecting control performance. The work is published in the journal Computers & Graphics.

When working with snow groomers, for example, the team from TU Graz found that data or VR headsets tend to be counterproductive, while information projected via a repurposed disco laser proved to be a great help.