PReWAP: Predictive Redirected Walking Using Artificial Potential Fields

In predictive redirected walking applications, planning the redirection and path prediction are crucial for a safe and effective redirection. Common predictive redirection algorithms require many simplifications and limitations concerning the real and the virtual environments to achieve a real-time performance. These limitations include for example that the tracking space needs to be convex, and only a single user is supported. In this paper, we present a novel approach called PReWAP which addresses many of these shortcomings. We introduce artificial potential fields to represent the real environment which are able to handle non-convex environments and multiple co-located users. Further, we show how this new approach can be integrated into a model predictive controller which will allow various redirection techniques and multiple gains to be applied.