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Drone Placement for Optimal Coverage by Brain Storm Optimization Algorithm

2018; Springer Nature; Linguagem: Inglês

10.1007/978-3-319-76351-4_17

2194-5357

Eva Tuba, Romana Capor Hrosik, Adis Alihodžić, Milan Tuba,

Robotics and Sensor-Based Localization

Unmanned aerial vehicles or drones are used in wide range of applications and one of them is area monitoring. Finding the optimal positions for drones so that the coverage is maximized, while reducing the fuel consumption represents computationally hard problem. For these kinds of problems, swarm intelligence algorithms have been successfully used. In this paper we propose recent brain storm optimization algorithm for finding the locations for static drones. Optimal drone placement maximizes the number of covered targets while minimizing drones altitude. The proposed method was tested in two different environments, with uniformly and clustered deployed targets. Based on the obtained results it can be concluded that brain storm optimization is appropriate for solving drone placement problem in both considered environments.