Route planning of an unmanned aerial vehicle using ant colony optimization for environment including a no-fly zone and obstacles

Abstract

The shortest route should be desired when considering flight time or battery capacity for an unmanned aerial vehicle (UAV) operation. Flight areas can include no-fly zones or obstacles that a UAV can avoid or fly over. This study addresses UAV route planning considering such no-fly zones and obstacles. We planned the routes of a UAV avoiding no-fly zones and flying over obstacles by ant colony optimization in computer simulations, then conducted the automated flight experiment on a real UAV based on the obtained routes, and confirmed the effectiveness of this approach. We show that the ant colony optimization devising program establishment can make possible UAV route planning for flight areas with no-fly zones and obstacles.