Three-dimensional UAV Path Planning Based on Modified Marine Predators Algorithm

WANG Wenju; HU Jie; CHEN Linzhouting; CHEN Ping

doi:10.12382/bgxb.2025.0537

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Three-dimensional UAV Path Planning Based on Modified Marine Predators Algorithm

更新时间：2026-04-24

- Three-dimensional UAV Path Planning Based on Modified Marine Predators Algorithm
- Acta Armamentarii Vol. 47, Issue 1, Pages: 250537(2026)
- 作者机构：
  
  贵州理工学院航空航天工程学院，贵州贵阳 550025
  贵州省水利投资（集团）有限责任公司，贵州贵阳 550000
  中国电子科技集团公司第二十八研究所空中交通管理系统全国重点实验室，江苏南京 210007
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2025.0537
  CLC： V249
- Received：24 June 2025，
  
  Online First：25 December 2025，
  
  Published：31 January 2026
- 稿件说明：
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WANG Wenju, HU Jie, CHEN Linzhouting, et al. Three-dimensional UAV Path Planning Based on Modified Marine Predators Algorithm[J]. Acta Armamentarii, 2026, 47(1): 250537.
DOI：

WANG Wenju, HU Jie, CHEN Linzhouting, et al. Three-dimensional UAV Path Planning Based on Modified Marine Predators Algorithm[J]. Acta Armamentarii, 2026, 47(1): 250537. DOI： 10.12382/bgxb.2025.0537.

摘要

针对复杂多重威胁环境下的无人机航迹规划问题，提出一种基于改进海洋捕食者算法（Modified Marine Predators Algorithm

MMPA）的求解方法。构建综合考虑无人机飞行最优性与安全性的多目标优化模型，并通过加权和方法将其转化为单目标优化问题。在标准海洋捕食者算法（Marine Predators Algorithm

MPA）框架下，引入新型自适应参数、非线性惯性权重、基于柯西分布的随机数生成和改进的位置更新规则4项创新机制，有效提升了算法的收敛速度与求解精度。通过15个基准测试函数的性能评估、4组不同复杂度的仿真场景以及真机验证实验，充分证明了MMPA在解决实际问题时所展现出的优越性与鲁棒性。

Abstract

To address the issue of unmanned aerial vehicle (UAV) path planning in complex multi-threat environments

a solution approach based on the modified marine predators algorithm (MMPA ) is proposed. A multi-objective optimization model is constructed

which comprehensively takes into account the flight optimality and safety of UAVs. This model is then converted into a single-objective optimization problem using the weighted sum approach. Four innovative mechanisms

i. e.

novel adaptive parameters

nonlinear inertia weight

Cauchy distribution-based random number generation

and an enhanced position update rule

are introduced under the framework of the standard marine predators algorithm (MPA) . These mechanisms effectively improve the convergence speed and solution accuracy of the algorithm. Through the performance evaluation on 15 benchmark functions

four groups of simulation scenarios with different complexities

and real-world validation experiments

it is adequately demonstrated that MMPA has the superiority and robustness when solving practical problems.

关键词

Keywords

references

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Related Institution

Unit 31827 of PLA

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