Multiobjective path planner for UAVs based on genetic algorithms

Abstract

This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Genetic Algorithms (GA) that obtains a feasible and optimal 3-D path for the UAV. It uses 9 different objective values which are calculated with a realistic model of the UAV and the environment and which are structured with 3 levels of priorities. Our planner works globally offline as well as locally online, which means that the algorithm can recalculate parts of the generated path in order to avoid unexpected risks. Finally, the effectiveness of the solutions given by this planner has been successfully tested against a simulator that contains the complete model of the UAV and the environment.