Influence of rotation gains on unintended positional drift during virtual steering navigation in virtual reality - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2024

Influence of rotation gains on unintended positional drift during virtual steering navigation in virtual reality

Résumé

Unintended Positional Drift (UPD) is a phenomenon that occurs during navigation in Virtual Reality (VR). It is characterized by the user's unconscious or unintentional physical movements in the workspace while using a locomotion technique (LT) that does not require physical displacement (e.g., steering, teleportation). Recent work showed that some factors, such as the LT used and the type of trajectory, can influence UPD. However, little is known about the influence of rotation gains (commonly used in redirection-based LTs) on UPD during navigation in VR. In this paper, we conducted two user studies to assess the influence of rotation gains on UPD. In the first study, participants had to perform consecutive turns in a corridor virtual environment. In the second study, participants had to explore a large office floor and collect spheres freely. We compared the conditions between rotation gains and without gains, and we also varied the turning angle to perform the turns while considering factors such as sensitivity to cybersickness and the learning effect. We found that rotation gains and lower turning angles decreased UPD during the first study, but the presence of rotation gains increased UPD in the second study. This work contributes to the understanding of UPD, which tends to be an overlooked topic and discusses the design implications of these results for improving navigation in VR.
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Dates et versions

hal-04771552 , version 1 (08-11-2024)

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Hugo Brument, Arthur Chaminade, Ferran Argelaguet. Influence of rotation gains on unintended positional drift during virtual steering navigation in virtual reality. 30th ACM Symposium on Virtual Reality Software and Technology (VRST), ACM, Oct 2024, Trier, Germany. pp.1 - 10, ⟨10.1145/3641825.3687734⟩. ⟨hal-04771552⟩
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