Collective Initial Excitation-Based Distributed Composite Adaptive Coverage Control With Application to a Network of Drones

In this letter, a collective initial excitation (C-IE) based distributed adaptive coverage control algorithm for a mobile sensor network (MSN) is proposed. The information exchange between agents is leveraged to collectively achieve the C-IE condition for parameter convergence. The C-IE condition is an extension of the previously established IE condition to the multi-agent setting. The C-IE has been shown to be milder than the collective persistence of excitation (C-PE), which is considered the state-of-the-art for parameter convergence in a multi-agent setting. In this letter, we present the first-of-its-kind composite control law that guarantees exponential convergence of the combined cost of coverage and parameter estimation. Simulation and experimental results involving multiple drones further validate the efficacy of the proposed concept.