NaviBoard and NaviChair: Limited Translation Combined with Full Rotation for Efficient Virtual Locomotion

  • Walking has always been considered as the gold standard for navigation in Virtual Reality research. Though full rotation is no longer a technical challenge, physical translation is still restricted through limited tracked areas. While rotational information has been shown to be important, the benefit of the translational component is still unclear with mixed results in previous work. To address this gap, we conducted a mixed-method experiment to compare four levels of translational cues and control: none (using the trackpad of the HTC Vive controller to translate), upper-body leaning (sitting on a "NaviChair", leaning the upper-body to locomote), whole-body leaning/stepping (standing on a platform called NaviBoard, leaning the whole body or stepping one foot off the center to navigate), and full translation (physically walking). Results showed that translational cues and control had significant effects on various measures including task performance, task load, and simulator sickness. While participants performed significantly worse when they used a controller with no embodied translational cues, there was no significant difference between the NaviChair, NaviBoard, and actual walking. These results suggest that translational body-based motion cues and control from a low-cost leaning/stepping interface might provide enough sensory information for supporting spatial updating, spatial awareness, and efficient locomotion in VR, although future work will need to investigate how these results might or might not generalize to other tasks and scenarios.

Export metadata

Additional Services

Share in Twitter Search Google Scholar Availability
Metadaten
Document Type:Article
Language:English
Author:Thinh Nguyen-Vo, Bernhard E. Riecke, Wolfgang Stuerzlinger, Duc-Minh Pham, Ernst Kruijff
Parent Title (English):IEEE Transactions on Visualization and Computer Graphics
ISSN:1077-2626
DOI:https://doi.org/10.1109/TVCG.2019.2935730
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=31443029
Publisher:IEEE
Date of first publication:2019/08/22
Submission status:Early Access
Tag:Adaptive Control; Cognitive informatics; Human computer interaction; Human factors; User interface; Virtual reality
Departments, institutes and facilities:Fachbereich Informatik
Institute of Visual Computing (IVC)
Entry in this database:2019/09/18