深入分析无人机路径规划,包括程序,算法,优化模型和新出现的挑战.
Muhammad Nafees1, Tamkeen Syeda1, Amjad Ali1
1Computer Science & IT, Karachi Institute of Economics and Technology, Karachi Sindh, Pakistan.
MethodsX
|March 11, 2026
概括
本研究回顾了无人机路径规划技术,包括算法和模型. 它强调了人工智能驱动的方法和对强大的导航系统的未来挑战.
科学领域:
- 机器人技术和自主系统
- 人工智能的人工智能
- 航空航天工程 航空航天工程
背景情况:
- 无人驾驶飞行器 (UAV) 对于监视,环境监测和交付至关重要.
- 有效的路径规划对于在复杂环境中自主无人机导航至关重要.
研究的目的:
- 为无人机路径规划研究提供全面的概述.
- 分析各种算法,问题模型和无人机导航中的新出现的挑战.
主要方法:
- 无人机路径规划技术的分类.
- 复习启发式,元启发式和人工智能驱动的算法.
- 评估算法的优点,弱点和问题模型.
主要成果:
- 详细分析传统,混合和人工智能驱动的路径规划方法.
- 确定关键挑战,包括实时处理和多UAV协调.
- 对各种应用程序的算法性能评估.
结论:
- 无人机路径规划是一个充满活力的领域,取得了重大进展.
- 未来的研究应该侧重于可扩展性,实时适应性和能源效率.
- 这一审查有助于研究人员开发先进的无人机导航系统.
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