Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2020
Abstract
We focus on the problem of simulating the haptic infrastructure of a virtual environment (i.e. walls, doors). Our approach relies on multiple ZoomWalls---autonomous robotic encounter-type haptic wall-shaped props---that coordinate to provide haptic feedback for room-scale virtual reality. Based on a user's movement through the physical space, ZoomWall props are coordinated through a predict-and-dispatch architecture to provide just-in-time haptic feedback for objects the user is about to touch. To refine our system, we conducted simulation studies of different prediction algorithms, which helped us to refine our algorithmic approach to realize the physical ZoomWall prototype. Finally, we evaluated our system through a user experience study, which showed that participants found that ZoomWalls increased their sense of presence in the VR environment. ZoomWalls represents an instance of autonomous mobile reusable props, which we view as an important design direction for haptics in VR.
Keywords
Encountered-type haptic devices, Immersive experience
Discipline
Graphics and Human Computer Interfaces | Software Engineering
Research Areas
Information Systems and Management
Publication
UIST '20: Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology, Virtual Conference, 2020 October 20-23
First Page
223
Last Page
235
ISBN
9781450375146
Identifier
10.1145/3379337.3415859
Publisher
ACM
City or Country
Virtual Conference
Citation
YIXIAN, Yan; TAKASHIMA, Kazuki; TANG, Anthony; TANNO, Takayuki; FUJITA, Kazuyuki; and KITAMURA, Yoshifumi.
ZoomWalls: Dynamic walls that simulate haptic infrastructure for room-scale VR world. (2020). UIST '20: Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology, Virtual Conference, 2020 October 20-23. 223-235.
Available at: https://ink.library.smu.edu.sg/sis_research/7969
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3379337.3415859