改进麻雀算法的无人机三维路径规划
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TP391.9 TP301

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国防基础科研计划;河北省重点研发计划;河北省高等学校科学技术研究项目(BJ2017041)


Uav 3D path planning based on improved Sparrow algorithm
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    摘要:

    为解决无人机在三维环境下的路径规划问题,本文通过麻雀搜索算法研究了路径规划方法。传统的麻雀搜索算法求解该问题时存在易陷入局部最优、收敛精度低等问题,针对该问题提出改进方法。首先,对种群中的发现者加入动态权重因子,使其能够提高局部搜索能力,同时提高收敛速度,同时引入高斯变异;追随者采用量子粒子群生成新解的方式;并且加入额外的柯西变异进行扰动,柯西变异的扰动幅度较小,可以增强局部搜索能力。通过仿真实验,.算法改进后分别与麻雀算法以及其他改进的麻雀算法进行对比,结果表明该算法收敛速度更快,求解精度更高,证明了该算法的有效性和可行性,可见在无人机三维路径规划中具有很大的发展前景。

    Abstract:

    In order to solve the path planning problem of UAV in 3D environment, this paper studies the path planning method by sparrow search algorithm. When the traditional sparrow search algorithm solves this problem, it is easy to fall into the local optimal and has low convergence accuracy. Firstly, the dynamic weight factor is added to the discoverer in the population to improve the local search ability, improve the convergence rate, and introduce Gaussian variation. Followers use quantum particle swarm to generate new solutions; And adding additional Cauchy variation to the disturbance, Cauchy variation perturbation amplitude is small, can enhance the local search ability. Through simulation experiments, the improved algorithm is compared with the Sparrow algorithm and other improved Sparrow algorithms respectively. The results show that the algorithm has faster convergence speed and higher solving accuracy, which proves the effectiveness and feasibility of the algorithm. It can be seen that the algorithm has great development prospects in the three-dimensional path planning of UAV.

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引用本文

吴学礼,王超,赵俊棋,等. 改进麻雀算法的无人机三维路径规划[J]. 科学技术与工程, 2024, 24(15): 6534-6542.
Wu Xueli, Wang Chao, Zhao Junqi, et al. Uav 3D path planning based on improved Sparrow algorithm[J]. Science Technology and Engineering,2024,24(15):6534-6542.

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  • 收稿日期:2023-06-05
  • 最后修改日期:2024-03-25
  • 录用日期:2023-10-20
  • 在线发布日期: 2024-06-04
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