A three-dimensional path planning method for unmanned aerial vehicles

By optimizing the path planning of unmanned aerial vehicles through an enhanced shared knowledge acquisition algorithm, the problems of local optima and slow convergence speed are solved, and fast global optimization path planning is achieved.

CN122408765APending Publication Date: 2026-07-17THE 28TH RES INST OF CHINA ELECTRONICS TECH GROUP CORP
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
THE 28TH RES INST OF CHINA ELECTRONICS TECH GROUP CORP
Filing Date
2026-04-10
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Traditional UAV path planning algorithms are prone to getting stuck in local optima, have slow convergence speeds, and cannot quickly obtain globally optimized paths.

Method used

An enhanced algorithm for acquiring shared knowledge is adopted. By randomly generating paths, using cubic spline interpolation to generate candidate paths, and combining knowledge factors and the principle of extreme values ​​to optimize the paths, the optimal path is generated.

Benefits of technology

It improves the convergence speed and accuracy of path planning, and can quickly obtain the global optimal solution, which is superior to traditional ant colony and particle swarm algorithms.

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Abstract

本发明公开了一种无人飞行器三维路径规划方法，包括：步骤1：获取无人机任务区域内的地理位置信息；根据事先规划的无人机任务区域获得三维地理位置信息，包括任务区域的经纬度和高程信息、边界信息，以及无人区域内的障碍物信息；步骤2：随机生成N条路径并得到相应的适应度值；步骤3：使用增强型获取共享知识算法对N条路径进行优化得到最优路径。使用增强型获取共享知识算法能够快速得到优化路径。在相同条件下与传统的算法比如蚁群算法、粒子群算法等相比较，仿真结果表明该算法在收敛速度、精度方面均有所提升。
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