Locomotion Techniques for Virtual Reality Omnidirectional Treadmills: An Evaluation on User Performance and Wayfinding

Abstract

Navigating virtual environments that exceed the boundaries of the physical space remains an open research challenge in Virtual Reality (VR) applications. In particular, rehabilitation and sports training require locomotion techniques that deliver realistic movement without compromising the user's navigation and wayfinding abilities. This thesis evaluates two VR omnidirectional-treadmill locomotion techniques, walk-in-place with the Kat VR and sliding with the Cyberith Virtualizer, and compares them against natural walking in an open space. Using a within-subject study with 18 participants who navigated a maze under each technique, user performance was assessed via metrics such as completion time, step count, and task load. Additionally, spatial understanding was evaluated by analyzing head-position and head orientation data, alongside post-trial sketch maps to measure spatial memory.

The results reveal that natural walking enables faster and more efficient navigation with lower physical exertion than the treadmill-based techniques, while yielding smoother and more continuous exploration. In contrast, walk-in-place and sliding produced more frequent stops, increased reorientation, and had a higher cognitive load. However, these additional cognitive demands did not significantly affect overall spatial memory, as determined by the post-trial sketches and head-tracking data. These findings demonstrate that although treadmill-based locomotion techniques may require more directional adjustments, they do not impair the user's ability to form accurate cognitive maps. The insights from both the user performance and spatial understanding studies provide valuable guidance for designing VR locomotion systems and developing intuitive interfaces that balance immersive movement with efficient spatial understanding.