Live path: adaptive agent navigation in the interactive virtual world

Abstract

We present a novel approach to adaptive navigation in the interactive virtual world by using data from the user. Our method constructs automatically a navigation mesh that provides new paths for agents by referencing the user movements. To acquire accurate data samples from all the user data in the interactive world, we use the following techniques: an agent of interest (AOI), a region of interest (ROI) map, and a discretized path graph (DPG). Our method enables adaptive changes to the virtual world over time and provides user-preferred path weights for smart-agent path planning. We have tested the usefulness of our algorithm with several example scenarios from interactive worlds such as video games. In practice, our framework can be applied easily to any type of navigation in an interactive world. In addition, it may prove useful for solving previous pathfinding problems in static navigation planning.