Motion Planning of Multiple Agents in Virtual Environments using Coordination Graphs

Abstract

Motion planning of multiple mobile agents in virtual environments is a very challenging problem, especially if one wants to plan the motions of these agents in real-time. We propose a two layered approach to plan motions of multiple mobile agents in real-time. The mobile agents are moving in a 2-dimensional static environment with open spaces connected to each other by narrow corridors. The global path of each agent is computed by a decoupled planner during the preprocessing process with minimum delay. Each agent’s local path is generated in real-time by combining steering behaviors and a new, principled and efficient AI technique for decision making and planning cooperative multi-agent dynamic systems, Coordination Graph (CG). With CG, we can not only avoid deadlocks in narrow corridors, but also achieve more complicated behavior such as leader-and-followers behavior. We show, via some preliminary examples, real-time performance of our approach, for instance, several robots avoiding deadlocks and successfully navigating a corridor.