A review of the application of optimization algorithms nature inspired in the design of flight paths

In this article, an overview of the application of optimization algorithms inspired by nature in the design of the flight path has been discussed. The significant increase in the capabilities and availability of independent ground and air tools makes safety and security challenges especially important in the protection of strategic infrastructure. In this context, the detection of multiple mobile threats with the aim of invading the limited spaces of these infrastructures is an important issue. This paper focuses on the trajectory planning problem for the interception of multiple aerial targets by a group of UAVs. 3D trajectory planning for the tracking of moving targets is a challenging task, especially when the tracking is performed by a crowd of UAVs, because there are numerous motion and dynamic constraints. The goal is to first assign targets to individual drones (task assignment) and create a 3D path for each one. Many algorithms are known as the main schemes to solve this kind of problems based on collective intelligence, many of them are based on biological systems such as particle swarm optimization, ant colony optimization, artificial bee colony optimization, bat-inspired algorithm, etc.