The coordination of cooperative unmanned aerial vehicles (UAVs) has become an active area of research. Approaches to coordinating these swarms often include a solution to a class of problems called Area Coverage. Problems in this class consist of obtaining information about a specific area of interest (usually a polygon or polyhedron) through a set of UAVs, usually with decentralized coordination and minimal human intervention. Area coverage problems model the requirements of different types of applications, such as in the case of emergencies and disasters, gas leak detection, rescue of lost people, among many others. Existing solutions to these problems usually consider a fixed set of UAVs. In this dissertation, a strategy to coordinate dynamic sets of UAVs to solve a specific Area Coverage problem is described. In these dynamic sets, UAVs can enter or leave the set. To implement the strategy, a framework was developed using ROS and Gazebo. The framework ROS is a set of libraries and tools for robots. Area Coverage missions are executed in the Gazebo simulation environment. The framework facilitates the implementation of different strategies for coordinating multiple UAVs. We introduced heat maps to assess the quality of the adopted strategy. A heat map represents the movement of UAVs in the plan.