Laboratory for Virtual Reality and Simulation (G006)

The lab has a wide range of hardware for MR applications.

THI-CAVE

The four-sided CAVE is a large-scale, projection-based system for VR simulation. The CAVE is a cubic space measuring 3 m x 3 m x 3 m. High-resolution stereoscopic projection on three walls and the floor provides a high degree of immersion for multiple users. A tracking system enables head tracking and 3D input. Thanks to the high computing power of the rendering cluster, even detailed CAD models with a high level of tessellation can be visualized.

VR Workstation

The lab has 12 VR workstations, each consisting of a high-performance desktop computer and a Meta Quest 3. Here, students can create and immediately test VR applications using game engines, either individually or in teams of two.

HoloLens

For augmented reality applications, the lab has two Microsoft HoloLens headsets.

VR Headsets

In addition to the Meta Quest 3 headsets, the lab has a variety of other VR headsets (HTC Vive (Pro), Oculus Rift CV/S, Samsung Odyssey), which can be loaned to students for academic projects.

Other Equipment

Smart depth cameras and motion capture suits can be used for applications requiring body tracking. 3D and high-speed cameras are used for generating HDRi textures or for analysis.

The following courses take place regularly: Projects (all faculty E and some faculty M courses), Practical Course MMI and Virtual Reality (FFI), Virtual and Augmented Reality (UXD), Practical Courses in technology of human-computer interaction and augmented and virtual reality applications(UXD).

Research in the VR Lab focused on the following areas:

Latency/Collaborative VR

Measuring latency in VR output devices and investigating the effects of latency on collaborative VR.

Collaborative VR = Collaboration among multiple people in a virtual environment

Latency = System-induced time delay between a user action registered by sensors and the update of a VR system’s output. High latency leads, among other things, to the dreaded cyber sickness.

AI-Based Pose Reconstruction

AI-based reconstruction of body poses using tracking data (head, hands, motion capture) as input.

Pose reconstruction serves as a starting point for further biomechanical analyses (e.g., ergonomics, muscle activation) and has a wide range of applications, including in gaming and sports medicine.

Riding Safety for Cyclists

VR simulations were used to investigate whether awareness alerts displayed on head-up displays can increase cyclists’ sense of safety, for example, when being passed by motor vehicles or when doors of parked vehicles open.