Roadmap-Based Flocking for Complex Environments

Flocking behavior is very common in nature, and there have been ongoing research efforts to simulate such behavior in computer animations and robotics applications. Generally, such work considers behaviors that can be determined independently by each flock member solely by observing its local environment, e.g., the speed and direction of its neighboring flock members. Since flock members are not assumed to have global information about the environment, only very simple navigation and planning techniques have been considered for such flocks. In this work, we investigate how the addition of global information in the form of a roadmap of the environment enables more sophisticated flocking behaviors. In particular, we study and propose new techniques for three distinct group behaviors: homing, exploring and shepherding. These behaviors exploit global knowledge of the environment and utilize knowledge gathered by all flock members. This knowledge is communicated by allowing individual flock members to dynamically update the shared roadmap to reflect (un)desirable routes or regions. We present experimental results showing how the judicious use of simple roadmaps of the environment enables more complex behaviors to be obtained at minimal cost. Animations of these behaviors can be viewed at http://parasol.tamu.edu.