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Three-Dimensional UAV Trajectory Planning Based on Improved Sparrow Search Algorithm
DOI:10.3390/sym17122071.png)
摘要
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无人机的任务能否成功完成取决于轨迹规划。三维环境下的无人机轨迹规划是一个复杂的全局优化问题,需要仔细考虑众多约束条件,包括山地地形、障碍物、禁飞区、安全高度、平滑度、飞行距离等。一般来说,从起点到终点的潜在空间多条轨迹中可以总结出对称性特征。针对Sparrow Search Algorithm (SSA)在三维对称轨迹规划中存在的种群多样性和局部优化等缺陷,结合正弦-余弦函数和Lévy flight策略,提出了Improved Sparrow Search Algorithm (ISSA),该算法通过动态调整搜索步长并增加偶发大步长跳跃,能够在更短时间内找到更优解,从而增强全局搜索与局部开发的对称平衡。为验证改进算法的有效性,将ISSA进行仿真并与Sparrow Search Algorithm (SSA)、Particle Swarm Algorithm (PSO)、Gray Wolf Algorithm (GWO)和Whale Optimization Algorithm (WOA)在相同环境下进行比较。结果表明,ISSA算法在收敛速度、路径成本、避障安全性及路径平滑度等关键指标上优于对比算法,能够在更少的迭代次数内获得更高质量的飞行路径。
Keyword:
unmanned aerial vehicle
three-dimensional trajectory planning
improved sparrow search algorithm
sine-cosine function
L & eacute
vy flight strategy
期刊
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IF:
2.2
论文数:
1.4K
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引用论文
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