LAUSR

The deployment and coordination of mobile sensor networks for coverage control applications can present several practical challenges, including how to efficiently share limited communication resources and how to reduce the use of localization devices (e.g., radars and lidars). One potential solution to these challenges is to reduce the frequency at which agents communicate or sample each other's position. In this article, we present a distributed asynchronous self-triggered control policy for centroidal Voronoi coverage control that is shown to decrease the sampling or communication instants among agents without degrading the performance of the mobile sensor network. Each agent independently decides when to sample the position of nearby agents and uses outdated information of its neighbors until new information is required. We prove that the locational cost function describing the distribution of agents monotonically decreases everywhere outside of a bounded neighborhood around the group's optimal configuration and that the agents asymptotically converge to their Voronoi centroids if the data-sampled centroid errors approach zero. In addition, we show that the sampling intervals are always positive and lower bounded and, as illustrated by simulations and experiments, they tend to stabilize at a large value as the mobile sensor network comes to a steady state. Simulations and experiments with ground vehicles validate the control strategy and show that the proposed policy can achieve similar level of performance as a continuous or fast periodic implementation.