基于量子粒子群优化的无人飞行器路径规划  

Unpiloted Aerocraft Path Planning Based on Quantum Particle Swarm Optimization

作　　者：过金超[1] 崔光照[1,2] 王延峰[1,2] 

机构地区：[1]郑州轻工业学院,郑州450002 [2]河南省信息化电器重点实验室,郑州450002

出　　处：《火力与指挥控制》2010年第12期31-33,37,共4页Fire Control & Command Control

基　　金：国家自然科学基金(60773122);河南省基础与前沿技术研究计划基金资助项目(092300410036)

摘　　要：根据地形障碍、敌方防御雷达、防空火力等威胁以及禁飞区的分布情况,引入最小威胁面的概念,利用B-Sp line插值逼近最小威胁面中的三维航迹在二维水平面内的投影,从而将三维曲线的规划问题简化为二维平面中控制点的寻优问题。采用量子粒子群优化算法,将约束条件和搜索算法相结合,有效解决了简单粒子群算法在高维空间中易陷入局部最优点的问题,简化了问题复杂度、提高了计算效率。仿真结果表明,生成的航迹具有地形跟随、障碍回避和威胁回避等功能。According to the threats distribution of terrain obstacles,adversarial defense radar sites and unexpected surface-to-air missile（SAM） sites,Surface of Minimum Risk is introduced and used to form the searching space.B-Spline curves are used to to approach the horizon projection of the 3-D route and this simplifies the original problem to a 2 dimension optimization problem.Quantum Particle swarm optimization is introduced to solve this optimization problem.Incorporating constrains into the algorithm,the local trap problem of simple PSO algorithm is solved effectively and the complexity of the optimization problem is decreased,efficiency is improved.The simulation results indicate the generated route has the function of terrain following,obstacle avoidance and threat avoidance.

关 键 词：无人飞行器 路径规划 量子粒子群优化 最小威胁面 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]