Unmanned aerial vehicle path planning problem by adjusted elephant herding optimization

Abstract

Unmanned aerial vehicle path planning is a high dimensional NP-hard problem. It is related to optimizing the flight route subject to various constraints inside the battlefield environment. Since the number of control points is large the traditional methods could not produce acceptable results when tackling this problem. Elephant herding optimization algorithm is one of the recent swarm intelligence algorithms which has not been sufficiently researched. In this paper we have adjusted the elephant herding optimization algorithm for the unmanned aerial vehicle path planning problem. We tested our approach using parameters of the battlefield environments from the literature and the comparative analysis has shown that our adjusted elephant herding optimization algorithm outperformed other approaches from the literature.