几何最佳导航和路径规划-桥梁理论,算法和应用
Hedieh Jafarpourdavatgar1, Samaneh Alsadat Saeedinia2, Mahsa Mohaghegh3
1Control Engineering Department, Amirkabir University, Tehran 1591634311, Iran.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
本研究回顾了自主系统的几何最佳导航和路径规划,整合了几何,优化和机器学习. 它强调了在动态环境中实现强大,高效的机器人导航的进步和挑战.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 计算几何和优化计算几何学
背景情况:
- 自主系统需要在复杂,动态的环境中高效,无碰撞的导航.
- 几何最佳导航和路径规划对于开发先进的机器人能力至关重要.
研究的目的:
- 系统地审查几何导航和路径规划中最先进的方法.
- 探索几何,优化和机器学习在自主系统中的整合.
- 确定当前的挑战,并为未来的研究提供框架.
主要方法:
- 关于几何导航和路径规划技术的综合文献综述.
- 分析持续优化,实时适应性和基于学习的策略的最新进展.
- 检查包括可扩展性,实时计算,感知集成和道德考虑在内的挑战.
主要成果:
- 几何原理,优化和机器学习的整合增强了机器人导航.
- 进步使机器人能够在动态环境中导航并避免移动的障碍物.
- 确定的主要挑战包括可扩展性,实时性能,感知和人机交互中的安全性.
结论:
- 几何学,优化和机器学习的整合为自主导航提供了一种新的方法.
- 解决已确定的挑战对于开发强大,高效和智能导航系统至关重要.
- 这项工作为未来的几何最佳导航和路径规划研究提供了路线图.
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