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在具有挑战性的环境中,改进了用于无人机交付路径规划的猪算法

Shenglin Liu¹, Zikai Jin², Hanting Lin¹

¹College of Science and Technology Ningbo University, Ningbo, Zhejiang, China.

Scientific reports

|September 3, 2024

概括

本研究介绍了用于无人机路径规划的改进的皇冠大黄猪优化器 (ICPO). ICPO增强了避难障碍和优化飞行路径,在复杂的地形上表现出卓越的性能.

科学领域:

无人机工程无人机工程
人工智能的人工智能
优化算法优化算法

背景情况:

传统的路径规划算法与复杂的环境作斗争,经常陷入局部最佳状态.
无人机技术的进步需要更高效,更强大的路径规划解决方案.
现有的方法在动态地形,避难障碍和能源消耗方面面临挑战.

研究的目的:

为改进无人机路径规划引入一个改进的皇冠大白猪优化器 (ICPO).
为了改善避难障碍,优化飞行路径,减少无人机的能源消耗.
在复杂和动态环境中解决传统算法的局限性.

主要方法:

改进的皇冠大猪优化器 (ICPO) 的开发灵感来自大猪的防御机制.
通过视听协同效应的前景,以改善早期的融合.
实施一个良好的点设定人口初始化战略,以增强多样性.
引入一种新的周期性撤退策略,以避免在后期阶段出现局部最佳状态.

主要成果:

ICPO证明了强度和稳定性,在IEEE CEC2022测试套件上实现了接近最佳的值.
在复杂的山地地形中,ICPO实现了778.1775和954.0118.18的最佳值.
在城市地形中,ICPO实现了366.2789和910.1682的最佳值,在比较算法中排名第一.
ICPO在无人机交付路径规划方面被证明是有效和可靠的.

结论:

改进的皇冠白优化器 (ICPO) 在无人机路径规划方面取得了重大进展.
ICPO有效地在复杂的地形上导航,增强安全性并优化能源消耗.
这种算法显示了未来无人机导航和配送服务应用的巨大潜力.

关键词:

复杂的环境复杂的环境改进的尖顶猪可以优化优化.路径规划路径规划路径规划无人机技术无人机技术

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