Application of dynamic ant colony algorithm in route planning for UAV

According to the characters such as complex constraint condition, multi uncertainty factors, real time demand for UAV route planning and the characters such as strong robustness, sub-optimal solution, easy implement for Dynamic Ant Colony Algorithm, This paper is applying the Dynamic Ant Colony Algorithm in route planning for UAV. Firstly, the characters of Dynamic Ant Colony Algorithm is analyzed Secondly, the modeling and processing for Dynamic Ant Colony Algorithm are described in detail. Thirdly, Dynamic Ant Colony Algorithm is applied in UAV reconnaissance scenario. And the DACA is realized in Matlab.

I. Introduction

Unmanned Aerial Vehicle (UAV) is a new type of combat platform with the ability of autonomous flight and perform task independently [1]. It can not only perform non attack missions, such as military investigation, surveillance, search and so on, but also perform attack missions, such as ground attack and bombing. With the rapid development of UAV technology, more and more UAV will be used in future battlefield.