Chaotic Cuckoo Search Algorithm for Solving Unmanned Combat Aerial Vehicle Path Planning Problems

Jeng-Shyang Pan, Jenn-Long Liu, Shou-Cheng Hsiung
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引用次数: 17

Abstract

This paper applies an improved Cuckoo Search algorithm, named Chaotic CS algorithm, to solve Unmanned Combat Aerial Vehicle (UCAV) path planning problems. A circle-type chaotic map for generating chaotic sequences is used to specify the scaling factor (() of step size and fraction probability (pa) of abandonment for host nests formulated in the Original CS algorithm. The advantage of using Chaotic CS algorithm can dynamically change the parameters of ( and pa by using the chaotic sequences over the course of iterations, resulting in an improvement for searching performance to find out the global best solution. The enhanced CS algorithm shows flexible and robust capabilities to optimize complex and multimodal objective functions by evaluating standard benchmark functions. Furthermore, the Chaotic CS algorithm is applied to solve complex design problem. Two scenarios of UCAV path planning problems are carried out for the practical applications. The simulation results indicate that the Chaotic CS algorithm can efficiently be used for computing optimal flight path of UCAV.
求解无人机路径规划问题的混沌杜鹃搜索算法
本文采用一种改进的布谷鸟搜索算法——混沌CS算法来解决无人作战飞行器(UCAV)的路径规划问题。使用生成混沌序列的圆形混沌映射来指定步长比例因子(()和原始CS算法中给出的宿主巢放弃分数概率(pa)。使用混沌CS算法的优点是可以在迭代过程中利用混沌序列动态改变(和pa的参数,从而提高搜索全局最优解的性能。改进的CS算法通过对标准基准函数进行评估,显示出对复杂多模态目标函数进行优化的灵活性和鲁棒性。并将混沌CS算法应用于复杂设计问题的求解。针对无人机的实际应用,给出了两种场景的路径规划问题。仿真结果表明,混沌CS算法可以有效地用于无人飞行器最优飞行路径的计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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