Q-Learning based system for Path Planning with Unmanned Aerial Vehicles swarms in obstacle environments

Alejandro Puente-Castro, Daniel Rivero, Eurico Farinha Pedrosa, Artur Pereira, Nuno Lau, Enrique Fernández-Blanco

Abstract: Highlights•Q-Learning for UAV swarm to determine the best flight path to cover the most area.•Estimate the flight paths on any size map with obstacles and without map information.•A system capable of calculating paths without the need for a smoothing stage.•Statistical comparison of a single ANN for each UAV against a global ANN for all UAVs.•An aircraI architecture-independent path optimization criterion.