# UAV Deployment Using Two Levels of Stigmergy for Unstructured Environments
## 3 Methods
### Description of the Swarm  
#### 3.1.1 The Individuals  
As discussed above, our work will focus on the use of pheromones to design various swarm behaviors capable of performing a deployment task in a structured environment. We will use a swarm robotics simulator, which we will detail later, to assess and validate these behaviors. We design a plausible physical swarm close to our physical robots. Then, we will describe the two types of individuals that will be modeled in our simulator.  
We will focus on two types of UAVs, which we will call micro informed (micro) and mini informed (mini), depending on the information and, therefore, the sensorization available to them. We consider vehicles that do not exceed 200 g and that range in size from 6 cm to a maximum of 25 cm. We will assume that the linear speeds they can achieve for safe indoor navigation do not exceed 1 m/s. Both types of drones have a flight control board that allows simple movement commands to be sent to the drone for later execution.  
The input commands may be high level (rotate 90\({}^{\circ}\), advance 1 m), similar to those used by the current consumer drones ([[https://www.parrot.com/](https://www.parrot.com/)]([https://www.parrot.com/](https://www.parrot.com/)), [[https://www.dji.com/](https://www.dji.com/)]([https://www.dji.com/](https://www.dji.com/))). To simplify the interface, we will assume that we can send a displacement vector to the drones with the information of the movement to be performed at a given moment and that the control board will adjust the state of the drone according to this information.  
Both types of drones use the same set of basic sensors. They will have IMU inertial unit data and a digital compass to obtain their orientation relative to north. These sensors are widely used and integrated by default in most control boards and commercial systems. In addition, the microdrones will have a barometric sensor (which makes it easy to stabilize the flight height), and the _mini_ drones will have an ultrasound system in addition to the barometric system, for low-altitude flight. The _mini_ drones also have a GPS tracking system, although it will not be used in this work since we intend to verify the behaviors presented here in indoor environments or where the GPS signal is not reliable.  
We also require the drones to be able to avoid indoor obstacles. We will assume that they have one of the many currently available avoidance systems, although due to the size of the devices the most appropriate system is visual navigation. We do not require high accuracy since we need only a repulsion vector to the area in the visual field of the drone that contains more obstacles.  
The drones can perform detection among themselves by using BLE beacons and know if they are near, far or out of range (for example, using the protocol established by Apple ibeacons ([[https://developer.apple.com/ibeacon/](https://developer.apple.com/ibeacon/)]([https://developer.apple.com/ibeacon/](https://developer.apple.com/ibeacon/)))). If they are close and in the field of vision, the obstacle avoidance system will return a repulsion vector toward the position of the detected drone. The microdrones will not have a relative location system, but the mindrones will. We will assume that they use a system similar to [3] that allows them to be located in the near space. The Bluetooth technology used for the location will also be used for short-range communications among drones. The autonomy of the drones will be fixed at 15 min of continuous flight. However, as will be discussed later, autonomy increases considerably if other tasks that save the energy consumed by the engines are performed.  
As will be seen later, the proposed pheromone system can be implemented directly with the drones described above without any additional sensors.