Distributed Event-Triggered Scalable Formation Control for Multiple Autonomous Vehicles

In this paper, we study the distributed formation control for agents modeled as a single integrator dynamics. We consider the problem of forcing a set of autonomous agents to move towards the desired trajectory that is only known by some leaders in the formation while forming a desired geometric pattern. The event-triggered mechanism in the communication is considered in the formation framework, where continuous communication among the agents is not required in this work, in the sense that the communication among the agents is restricted in a way that it provides a decentralized scheme for scheduling information broadcast for each agent independently from other neighboring agents. Under this theoretical scheme, analysis demonstrates that under the proposed controller, all closed-loop signals are bounded and the Zeno behavior is avoided. Furthermore, the tracking error will converge asymptotically to the origin. Building on this event-triggered controller, an algorithm is proposed to guarantee safe navigation of the agents from colliding when entering unexpected spatial constraints, in such a way the formation scaling factor is updated to scale up or scale down the size of the formation in the case that the region is impassable for the group of agents with the original formation size..