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.