Abstract
Redirected walking allows users to naturally walk in virtual environments that are larger than their physical surroundings by subtly steering them around real-world obstacles. Alignment-based controllers, such as Vis.-Poly. and Alignment-Optimized, have demonstrated potential in minimizing collision occurrences. However, the assessment of shape similarity using polygonal area has weakened the performance of these controllers since area similarity fails to differentiate between regions with same area but different shapes. This paper presents a weighted area method for approximating the area of a walkable region in front of the user. The area of a walkable region can be estimated by accumulating the subdivided unit areas that intersect the region. These unit areas are assigned weights based on the user's location and orientation. Moreover, Artificial potential fields (APF) value at the center of each unit can be easily incorporated into the weight computation. In a simulation-based evaluation, the Alignment-Optimized controller, implemented using the weighted area method, both without and with the APF value-dubbed as Alignment-Optimized-WA-(AD) and Alignment-Optimized-WA-(AD+APF), respectively-is compared against top-notch controllers including Alignment-Optimized, Vis.Poly., ARC, Alignment+APF-Optimized, APF-S2T, and APF-S2G. The results reveal that both Alignment-Optimized-WA-(AD) and Alignment-Optimized-WA-(AD+APF) exceed the performance of these cutting-edge controllers.