Coverage control of multiple ocean vehicles for environment monitoring with energy constraints

A coverage control algorithm in unknown environment is proposed for the multi-vehicle systems in this paper. The measurement white-noise is taken into consideration while learning the interest information online. The Kalman Filter (KF) is introduced to eliminate the noise disturbance and provide us a set of accurately sampled-data. Then, we describe an adaptive algorithm to approximate the sensory function by using the sampled-data from KF. A decentralized adaptive control architecture is proposed to drive the vehicles converge to the optimal coverage configuration with the estimated Voronoi Centroids. Finally, simulations are carried out to demonstrate the adaptive estimation algorithm and show us that the multi-vehicle systems will converge to the optimal coverage configuration.