Model based adaptive coverage control for multiple autonomous underwater vehicles

The model adaptive coverage control problems with unknown model parameters are studied. A novel model based adaptive coverage control strategy for multi-autonomous underwater vehicle (AUV) systems is proposed such that the coverage network would converge to the optimal deployment. Firstly, according to the proposed cost function and the Voronoi partition, the mission region is divided into subregions optimally with respect to the multi-AUV systems. Using this region partition and model based adaptive control as the theoretical foundation, an optimal adaptive coverage control algorithm with unknown model parameters is proposed to deploy the coverage network to the optimal positions. Finally, numerical simulations are provided to illustrate the feasibility and effectiveness of the proposed approaches.