基于改进蚁群算法的飞行器航迹规划研究
Research on Path Planning for Flight Vehicles based on Improved ACO
李荣晟 1杨小龙 2严晞隽 1任天助1
作者信息
- 1. 北京宇航系统工程研究所,北京,100076
- 2. 中国运载火箭技术研究院,北京,100076
- 折叠
摘要
针对蚁群算法在进行航迹规划时存在收敛较慢、易陷入停滞、转弯过多且角度大等问题,提出一种应用于飞行器二维航迹规划的改进蚁群算法.通过优化邻域扩展方式加速收敛,改进信息素生效策略,以提高蚁群对信息素的利用率,防止陷入停滞,引入局部优化修正航迹,减小航迹曲折程度.仿真结果表明,改进算法在收敛性、迭代次数、航迹质量等方面具有一定优势,证明改进措施提升了蚁群算法收敛速度及规划航迹质量.
Abstract
An improved ACO is proposed for two-dimensional path planning of flight vehicles to solve the problems such as slow convergence speed,easy to fall in stagnation and zigzag path with large angles in basic ACO.First,the improved algorithm optimizes extend method to accelerate convergence.Then,a new pheromone strategy is put forward to increase the utilization of pheromone information while preventing ant from falling into stagnation.At last,local optimization method is introduced to reduce the twists and turns in the searched path.According to the simulation results,the improved ACO has superiority in convergence,iteration number and quality of path.The result proves that the improved algorithm can increase the rate of convergence and path quality compared with basic ACO.
关键词
航迹规划/改进蚁群算法/局部优化/航迹质量/收敛速度Key words
path planning/improved ACO/local optimization/quality of path/rate of convergence引用本文复制引用
出版年
2024
NETL
NSTL
万方数据