Dynamic Coverage Control for Constrained Mobile Sensor Networks

In this article, we study the cooperative dynamic coverage control problem by using viability theory. We focus on the intertemporal coverage optimization for nonlinear mobile sensor networks with mobility constraint, arbitrary sensory range, and obstacle avoidance over large-scale domains, which remains to be an interesting open problem prior to this work. Our proposed cooperative coverage control law enables the constrained sensor networks to minimize the overall intertemporal cost of the distributed attention factors throughout the mission domain, while avoiding unforeseen obstacles, by just local information. The mobility constraint of the mobile sensors includes nonzero velocity and bounded turning rate, where the unforeseen obstacles, the mission domain, and the sensory range are considered to be arbitrary compact sets. The viable detection domain is proposed based on viability theory, which is the largest set of states within the sensory domain, and the designed control strategy enables the mobile sensor to detect any target point inside it in a finite time while avoiding obstacles. Effective algorithms capable of reconstructing the viable detection domain are derived, with which both the noncooperative and cooperative coverage control strategies are developed, and their corresponding coverage performances are analytically evaluated. The efficiency of the proposed method is confirmed and illustrated via simulations.