## 2 Proposed Architecture
### Layer I: Global Path Planner  
The first layer of architecture is fully related to a key aspect within the autonomous movement of unmanned systems, such as path planning. The implemented path planner relies on both two-dimensional and three-dimensional information to establish, for each swarm agent, an optimal and secure path. To do this, from previous information of the environment, an exploration of the environment is carried out by using an algorithm based on Probabilistic Road Maps (PRM), which allows efficiently to establish, on an area of interest, a set of possible paths, free of collisions, on which to perform a safe autonomous navigation. The use of this algorithm allows, against other methods of planning trajectories collected in the literature, to perform the exploration of large environments in a short period of time and, generate as an output a graph with all possible paths to be traveled. This unique and fast exploration of the environment allows you to establish a highly  
Figure 1: General scheme of the proposed autonomous Unmanned Aerial Vehicle (UAV) swarm. scalable path planner for use in swarms of UAVs made up of a variable number of agents. Together with the PRM algorithm in charge of exploration, the A* algorithm is used to generate an optimal solution, in terms of total distance traveled, in such a way that, from the set of possible paths, establish, for each UAV, that path that allows it to reach a destination location traveling as little distance as possible [21; 22]. This path planner not only has the advantage of being able to generate an optimal solution for a scalable number of UAVs or, being able to work with information in two or three dimensions of the environment, but also contemplates the possibility of being used for different situations such as: a labeled case, in which the location to which each swarm agent must go is previously known; an unlabeled case, for which the proposed path planner not only generates the paths, but is previously responsible for establishing which combination UAV target locations minimizes the total distance traveled by the swarm by using the Hungarian method; Finally, in order to be able to undertake, in the future, firefighting work optimally with a swarm of UAVs, the proposed path planner, allows to establish the final positions each swarm agent within a specific geometric formation and then establish the set of optimal and safe trajectories so that each UAV reaches its position within the formation. While it is true that, the type and number of formations that a swarm of UAVs can achieve is very extensive and diversified, these three types of specific formations have been established in this work as the application of the swarm to work and work related to the fight against fire and possible tasks of extinguishing them have been established. Forest firefighting is often linked to attacking and extinguishing combustion that usually spread uncontrollably over a plant and open area [23]. It is important to note that forest fires can be generated under a set of various geometric shapes, among which are some regular shapes such as circles or ellipses, and whose properties are determined by aspects such as weather conditions, orography, or variation in fuel type [24; 25]. In the case of circular fires, the front of the fire is deployed in all directions from the central area to the outside [26], so the square formation, with a size and perimeter greater than the diameter of the circle of fire, would allow to act on the fire, avoiding its propagation and helping to control and reduce it (Figure 2). Figure 2: Action in square formation in front of a fire with a circular shape. In the case of fires with an elliptical shape, they are characterized because the propagation is affected by a wind with a predominant direction [26]. In this case, when the fire advances towards a specific direction, having an arrow formation allows to act in an incisive way on the area of growth and advance of the fire.