人工蜂群算法的无人机航路规划与平滑  

Smooth trajectory planning of an unmanned aerial vehicle using an artificial bee colony algorithm

作　　者：刘敏[1,2] 邹杰[1,2] 冯星[1,2] 赵振宇[1,2] 

机构地区：[1]光电控制技术重点实验室,河南洛阳471009 [2]中航工业洛阳光电设备研究所,河南洛阳471009

出　　处：《智能系统学报》2011年第4期344-349,共6页CAAI Transactions on Intelligent Systems

基　　金：总装重点实验室基金资助项目(9140C460104091301)

摘　　要：航路规划是无人机(UAV)作战任务规划系统的关键组成部分,目标是在适当的时间内为UAV计算出最优或次最优的飞行航路.人工蜂群(ABC)算法是一种最新发展的模拟昆虫王国中蜜蜂群体寻找优良蜜源的群体智能优化算法.采用人工蜂群算法完成无人机的平滑航路规划,首先阐述了人工蜂群算法的基本原理,然后将无人机航路规划问题通过建模转换成为一个多维函数优化问题,利用人工蜂群算法的优势,找到多维函数的最优解,最后对优化后的航路进行了平滑,使UAV对规划后的航路可飞.仿真实验结果表明,此方法可有效规划出航路,且所规划的航路可飞.Trajectory is a key issue for an unmanned aerial vehicle （ UAV）, which aims to obtain an optimal or sub- optimal trajectory within proper time. The artificial bee colony （ABC） is a new algorithm based on how a bee colo- ny finds food. On the basis of introducing the basic principle of the ABC, and the description of threatening models of a UAV, the UAV trajectory planning was transformed into an optimization problem through modeling. Then the optimal solution of the multi-dimensional function was given by taking advantage of the artificial bee colony algo- rithm. Finally, the smoothing strategy was adopted to obtain a feasible path. The feasibility and effectiveness of the proposed approach was verified by experimental results.

关 键 词：无人机 航路规划 人工蜂群算法 平滑 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] V19[自动化与计算机技术—控制科学与工程]