Online path planning for uav navigation based on quantum particle swarm optimization

Abstract

With regard to modern warfare, the environmental information is changing and it's difficult to obtain the global environmental information in advance, so real-time flight route planning capabilities of unmanned aero vehicles (UAV) is required. Quantum Particle Swarm Optimization (QPSO) is introduced to solve this optimization problem. Meanwhile, According to the threats distribution of terrain obstacles, adversarial defense radar sites and unexpected surface-to-air missile (SAM) sites, Surface of Minimum Risk (SMR) is introduced and used to form the searching space. The objective function for the proposed QPSO is to minimizing traveling time and distance, while exceeding a minimum pre-defined turning radius, without collision with any obstacle in the flying workspace. Quadrinomial and quintic polynomials are used to approach the horizon projection of the 3-D route and this simplifies the original problem to a two dimension optimization problem, thus the complexity of the optimization problem is decreased, efficiency is improved. The simulation results show that this method can meet online path planning. © 2012 Springer-Verlag Berlin Heidelberg.