# UAV Deployment Using Two Levels of Stigmergy for Unstructured Environments
###### Abstract
For example, in [18], stigmergy is used in a behavior to search for a target. This behavior requires all the agents to use global location to be able to perceive and place virtual pheromones in a specific location. However, such systems cannot be used indoors (signal reception occlusion) or in all outdoor locations and situations [19], so another approximation, such as local localization, must be considered. Robot local localization commonly requires environment maps and odometry sensing [20]. Environment maps may be unavailable, and the online creation of maps requires powerful processing that may not be available on small flying robots [4; 21]. Furthermore, such approaches do not scale appropriately with large swarms [22]. Moreover, there are simple relative localization applications that are suitable for small UAVs; for example, in [23] presents the relative positioning of sensors in reference to nearby static robots with a decentralized approach. Nowadays, one of the main technologies required to make the leap from flying a single UAV to flying a decentralized swarm is an accurate and reliable intra-swarm relative localization technology [4]. One of the first applications related to UAV deployment can be found in [24]. This application uses a predetermined communication network as the basis for guiding UAVs. Although this behavior does not require an external communications network, it does need a predeployment phase, as in the terrestrial application in [5], which is not applicable in real emergency situations. In a later work, in [25] reconfigures the network of sensors to maximize system performance, but the method requires a group of terrestrial robots to transport the sensor network, which is not practical for our needs. More recently, ref. [23; 26; 27] present several behaviors where a fully distributed deployment is achieved while creating a communication network. These systems do not require existing communication networks or a global localization system. In addition, it is an effective strategy that is designed to save energy when using UAVs, which is very important for increasing swarm autonomy. in [23; 27] assume that a robot can temporarily attach to the ceiling or land on the ground for efficient surveillance over extended periods of time. However, as the authors discuss, this behavior requires special environment features (straight walls, 90 degree angles, etc.) to be executed (it is not applicable for unstructured environments) and does not take into account uncertainty (for example, the errors in sensor readings and robot actuators), which is very important in UAVs systems. Using the ideas presented in [23; 26; 27; 28; 29], a UAV swarm can establish their own communications network. This network can be used for communicating swarm tasks or even to help other robots or a human team with subsequent work [5; 10; 11; 24; 30; 31]. In this paper, we will present a behavior inspired by the work of [28], in terms of establishing their own network of communications, and by [23; 27], in terms of adapting the behavior to UAVs using a power saving state. However, in contrast to previous articles, our distributed behavior will be executable in any environment, without limitations on the specific features or size. For this purpose, a virtual sematectonic stigmergy system will be used. The use of this type of communication is not novel in the field of swarm robotics; the literature contains several applications using stigmergy as a communication mechanism. In [32], swarm behavior that can develop collaborative tasks through sematectonic stigmergy is presented. ref. [33] discusses a theoretical approach to the use of stigmergy in UAVs using stigmergy potential fields. To implement this type of communication, it is assumed that we have a local positioning mechanism [4] and a efficient system of communication between individuals, for example, the use of mesh networks of XBEEs devices [34].