Three dimensional path planning of UAV based on adaptive particle swarm optimization algorithm

Abstract

Aiming at the problem of falling easily into local optimal solution of conventional particle swarm optimization algorithm, an adaptive particle swarm optimization algorithm is proposed, which adaptively adjusts the values of inertial weight and two learning factors in the iterated search process. The environment model of path planning is built for unmanned aerial vehicle (UAV) to perform reconnaissance task in mountain environment. The self-constraint conditions of UAV are analyzed. The fitness degree function of adaptive particle swarm optimization algorithm and flow chart of path planning algorithm are designed. The simulation experiments of three dimensional path planning of UAV are carried out by adopting respectively the adaptive particle swarm optimization algorithm and the conventional particle swarm optimization algorithm. The contrast of simulation result shows that the proposed adaptive particle swarm optimization algorithm has higher global search ability and search precision than the conventional particle swarm optimization algorithm.