Randall W. Hill, Jr., Changhee Han, and Michael van Lent, USC Institute for Creative Technologies
This paper describes a method for building a cognitive map of a virtual urban environment. Our routines enable virtual humans to map their environment using a realistic model of perception. We based our implementation on a computational framework proposed by Yeap and Jefferies (1999) for representing a local environment as a structure called an Absolute Space Representation (ASR). Their algorithms compute and update ASRs from a 2-1/2D sketch of the local environment, and then connect the ASRs together to form a raw cognitive map. Our work extends the framework developed by Yeap and Jefferies in three important ways. First, we implemented the framework in a virtual training environment, the Mission Rehearsal Exercise (Swartout et al. 2001). Second, we describe a method for acquiring a 2-1/2D sketch in a virtual world, a step omitted from their framework, but which is essential for computing an ASR. Third, we extend the ASR algorithm to map regions that are partially visible through exits of the local space. Together, the implementation of the ASR algorithm along with our extensions will be useful in a wide variety of applications involving virtual humans and agents who need to perceive and reason about spatial concepts in urban environments.