A Redirected Walking Toolkit for Exploring Large-Scale Virtual Environments
PubDate: March 2022
Teams: Shandong Normal University
Writers: Yunqiu Liu; Jia Cui; Meng Qi
Redirected walking (RDW) has been shown to be a feasible solution that allows users to explore large-scale virtual environments (VEs) by walking in the real world. However, wide adoption of this technique has been hindered by the complexity and subtleties involved in redirecting users to avoid collisions with real-world boundaries and obstacles in a room-scale space. To address this problem, we develop a redirected walking toolkit to serve as a universal toolkit for general users and researchers to deploy and benchmark various RDW algorithms in a room-scale physical space. In this toolkit, we adopted both reactive and predictive RDW algorithms. When the user inevitably reaches a physical boundary, our toolkit uses multimodal human-computer interaction to reorientate the user, so that the users can safely remain within the tracked space boundaries. Results with both simulated and live-user experiments indicate that our toolkit combines affordability, robustness, and practicality while providing presence and effectiveness for large-scale virtual exploration in virtual reality (VR) applications.