Particle swarm optimization method for the control of a fleet of Unmanned Aerial Vehicles

International audienceThis paper concerns a control approach of a fleet of Unmanned Aerial Vehicles based on virtual leader. Among others, optimization methods are to develop the virtual leader control approach, particularly the particle swarm optimization method (PSO). The goal is to find the best positions at each instant of each UAV to optimize the performance of a given task by minimizing a predefined objective function. The UAVs are able to organize themselves on a 2D plane in a predefined architecture, following a mission led by a virtual leader and simultaneously avoiding the collisions between the different vehicles of the group. The global proposed method is independent from the model or the control of a particular UAV. The method is tested in simulation on a group of UAVs whose model is treated as a double integrator. Test results for the different cases are presented