| 摘 要: 针对空中三维障碍环境下的无人机飞行路径规划问题,提出一种基于改进的水鹰优化算法的动态无人机路径规划策略。设定一空中障碍点模拟空中飞行物,采用多维分段混沌映射初始化飞行路径群。引入自适应参数调整机制和多目标优化策略,实现最短路径和最快计算的综合目标。采用直线路径优先和贝塞尔曲线拟合路径的方式提升实际飞行路径的流畅度。实验结果表明,改进水鹰优化算法的迭代路径更短,迭代收敛速度更快,能有效处理无人机三维空中避障的路径规划问题。 |
| 关键词: 水鹰优化算法 三维路径规划 策略优化 贝塞尔曲线 多维分段混沌映射 |
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中图分类号: TP391.4
文献标识码: A
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| 基金项目: 江苏省自然科学基金项目(BK20240607);江苏省高等学校自然科学研究项目(24KJD110005) |
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| Three-Dimensional Obstacle Avoidance Strategy for Aerial Drones Based on Prompt Water Eagle Optimization Algorithm |
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XIAO Lili, JIANG Haibo
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(College of Science, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)
xll@njupt.edu.cn; 20230081@njupt.edu.cn
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| Abstract: To address the path planning problem for unmanned aerial vehicles (UAVs) in three-dimensional obstacle-filled environments, this paper proposes a dynamic UAV path planning strategy based on Prompt Water Eagle Optimization ( PWEO) algorithm. First, aerial obstacle points are set to simulate flying objects. Subsequently,multidimensional piecewise chaotic mapping is employed to initialize the flight path population. An adaptive parameter adjustment mechanism and a multi-objective optimization strategy are then introduced to achieve the dual goals of shortest path and fastest computation. Finally, the strategy prioritizes straigh-t line paths and utilizes Bézier curve fitting to enhance the smoothness of actual flight trajectories. Experimental results demonstrate that the improved SHO algorithm generates shorter paths, converges faster, and effectively handles 3D aerial obstacle avoidance in UAV path planning. |
| Keywords: Water eagle optimization algorithm 3D path planning strategy optimization Bézier curve multidimensional piecewise chaotic mapping |
