Exploring Bi-Manual Teleportation in Virtual Reality

TL;DR

This study investigates bi-manual teleportation techniques in VR, demonstrating improved speed and accuracy over uni-manual methods, and introduces a new Fitts' Law model to better predict user performance.

Contribution

The paper introduces a novel bi-manual teleportation method, evaluates its performance with a user study, and proposes an improved Fitts' Law model for VR interactions.

Findings

Bi-manual techniques enable faster teleportation with dominant hand pointing.

Bi-manual and dwell methods are more accurate than uni-manual approaches.

A new Fitts' Law variation better predicts VR teleportation performance.

Abstract

Teleportation, a widely-used locomotion technique in Virtual Reality (VR), allows instantaneous movement within VR environments. Enhanced hand tracking in modern VR headsets has popularized hands-only teleportation methods, which eliminate the need for physical controllers. However, these techniques have not fully explored the potential of bi-manual input, where each hand plays a distinct role in teleportation: one controls the teleportation point and the other confirms selections. Additionally, the influence of users' posture, whether sitting or standing, on these techniques remains unexplored. Furthermore, previous teleportation evaluations lacked assessments based on established human motor models such as Fitts' Law. To address these gaps, we conducted a user study (N=20) to evaluate bi-manual pointing performance in VR teleportation tasks, considering both sitting and standing postures. We proposed a variation of the Fitts' Law model to accurately assess users' teleportation performance. We designed and evaluated various bi-manual teleportation techniques, comparing them to uni-manual and dwell-based techniques. Results showed that bi-manual techniques, particularly when the dominant hand is used for pointing and the non-dominant hand for selection, enable faster teleportation compared to other methods. Furthermore, bi-manual and dwell techniques proved significantly more accurate than uni-manual teleportation. Moreover, our proposed Fitts' Law variation more accurately predicted users' teleportation performance compared to existing models. Finally, we developed a set of guidelines for designers to enhance VR teleportation experiences and optimize user interactions.