Distributed coverage control under generalized locational optimization framework

Distributed coverage control is an essential problem for search and exploration in networked environments. In this paper, we start with generating a conventional locational optimization method for both homogeneous and heterogeneous UAV/UGV groups with reality constraints (e.g., connectivity maintenance and collision avoidance), covering both convex and non-convex environment. Then, we develop several coverage control strategies using mixed cost functions for RSS-based, vision-based, and probability-based sensor networks in 3D environments. The control algorithms motivated by distributed constraint optimization and guaranteed convergence are then proved on the tenet of Leibnitz theory and LaSalle´s invariance principle. Lastly, several simulation examples are used to demonstrate the application of design procedures.