UAV path planning based on an elite-guided orthogonal diagonalised krill herd algorithm

Abstract

At present, obstacle avoidance and the shortest path to the destination are the main problems that need to be considered when the UAV (unmanned aerial vehicle) performs its mission. In this paper, an Elite-Guided Orthogonal Diagonalised Krill Herd (EODKH) algorithm is developed to solve the path planning problem of UAV in three-dimensional space with complex terrain. EODKH algorithm divides the krill population into two parts: one part is composed of elite krill, and the evolution of krill population is guided by the experience of elite krill with orthogonal diagonalisation, and the elite krill with higher rank can obtain greater 'respect' in the evolution procedure; the other part evolves according to the original krill herd method, so as to improve the convergence diversity of the whole krill herd. Experimental results show that EODKH is better than other krill herd algorithms in UAV path planning.