Performance comparison of particle swarm optimization and Cuckoo search for online route planning

The popularity of unmanned aerial vehicles (UAV) has been constantly increasing during the last years. After being used as war tools by armies around the world, UAVs started being used in multiple civil applications. In the near future, hundreds or even thousands of UAVs will share the airspace with civil and commercial aviation [1]. Hence, UAVs become a new risk factor to consider in aerial security [2]. In this context, the need for researching and developing new intelligent systems capable of reducing the risks is justified. These intelligent systems must be able to optimize and update their flight trajectories to avoid collisions with buildings, mountains, or other airships. Therefore, the route planning method has real-time requirements. It must obtain the UAV orientation in real time, not only to reach the target but also to avoid collisions. The problem increases when the environment changes dynamically or when there is not a predefined flight route to follow [3].