An Adaptive Vision-Based Approach to Decentralized Formation Control

Abstract

In considering the problem of formation control in the deployment of intelligent munitions, it would be highly desirable, both from a mission and a cost perspective, to limit the information that is transmitted between vehicles in formation. We have proposed an adaptive output feedback approach to address this problem. Adaptive formation controllers are designed that allow each vehicle in formation to maintain separation and relative orientation with respect to neighboring vehicles, while avoiding obstacles. We have implemented two approaches for formation control, namely, leader-follower formations and leaderless formations. In leader-follower formations, there is a unique leader and all the other vehicles are followers. In leaderless formations, there is no unique leader. Each vehicle tracks line-of-sight range to up to two nearest vehicles while simultaneously navigating towards a common set of waypoints. As our results show, such leaderless formations can perform maneuvers like splitting to go around obstacles, rejoining after negotiating the obstacles, and changing into line-shaped formation in order to move through narrow corridors.