# UAV Deployment Using Two Levels of Stigmergy for Unstructured Environments
## 4 Results
### LTID Tests  
Figure 12 presents the results of 600 simulations performed for SLABE and SEPHE using the LTID strategy for different take-off time intervals on _easy_ maps. For each take-off value, 50 random maps and random take-off positions are generated. For both behavior types, the figure shows the average and standard deviation of the number of collisions, the time required to cover the 95%of the environment, the energy consumed and the total flight time required by the active members of the swarm. Figure 12: Results of the SLABE (**a**) and SEPHE (**b**) behavior simulations performed on 50 random _easy_ maps. In each simulation, a random start position has been chosen among all feasible locations. Six different take-off time intervals have been tested for each map (6, 8, 10, 12, 18, and 24 s). The average and standard deviation of the number of collisions, the time required to cover 95% of the environment, the energy consumed by the swarm, and the total flight time are shown. At a general level, it is easy to see how the minimum time required to reach the desired coverage (approximately 16 min) is achieved with a take-off time interval of 6 s (the shortest used). However, the shorter interval also increases the number of collisions between vehicles. The energy required by the swarm starts at 2000 kW for a take-off time interval of 6 s and decreases to 1000 kW as the time interval increases. This decrease is significant for the initial interval and becomes much less pronounced for an interval of 12 s. The same is not true for the deployment time, which increases continuously from the initial 6 s take-off interval (and 16 min deployment) to the 24 s take-off interval (and 30 min deployment) for the SLABE behavior. The general tendencies are the same for both types of behavior: less energy is consumed and fewer collisions occur as the take-off time interval increases. There is much greater variability in the total flight time required and in the energy consumed for the SLABE strategy. Figure 13 presents the results of 600 simulations for both types of behavior (SLABE and SEPHE) using the LTID strategy for different take-off time intervals on _hard_ maps. The parameters used in the tests are the same as in the previous case. The time required for deployment is much longer than that of the previous case (a minimum of approximately 40 min), which is a consequence of the size of the map and the greater difficulty of navigation. The general tendencies observed in the previous case are maintained: the shorter the take-off time interval, the greater the number of collisions and the shorter the time require to achieve the desired coverage. However, the decrease in energy is not as substantial as that in the previous case. Energy consumptions remains almost constant, even for smaller take-off time intervals. The coverage  
Figure 13: Results of the SLABE (**a**) and SEPHE (**b**) behavior simulations performed on 50 random _hard_ maps. In each simulation, a random start position has been chosen among all feasible locations. Six different take-off time intervals (6, 8, 10, 12, 18, and 24 s) have been tested for each map. The average and standard deviation of the number of collisions, the time required to achieve 95% coverage, the energy consumed by the swarm and the total flight time are shown. times of the two approaches are similar, although there is still much more variability in the flight time required by the SLABE strategy. Although the behaviors have been executed on the same type of agents, the SLABE behavior has much lower hardware requirements for its implementation; therefore, the agents that support it do not require higher energy consumption. Figure 14 presents a simulation of the SLABE and SEPHE behaviors equivalent to the previous one but with a different energy model for the SLABE agents. In this case, the agents executing this behavior require 15 W in the active state (equivalent to the consumption of vehicles of the ARDrone type) and 0.5 W in the beacon state.