移动机器人自主导航的障碍回避和路径规划方法
Kornél Katona1, Husam A Neamah1, Péter Korondi1
1Department of Electrical Engineering and Mechatronics, Faculty of Engineering, University of Debrecen, 4028 Debrecen, Hungary.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
本文回顾了机器人和自动驾驶汽车的避障算法. 它涵盖了古典和现代技术,以确保在动态环境中安全导航和防止碰撞.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 自主导航系统 自主导航系统
背景情况:
- 路径规划对于机器人导航环境和到达目的地至关重要.
- 避免障碍物是路径规划的关键组成部分,确保无碰撞的自主运行.
- 有效的避障算法对于机器人和自动驾驶汽车的安全和高效运行至关重要.
研究的目的:
- 为机器人技术中关键的避障算法提供全面的概述.
- 分析各种避障技术的优点,局限性和应用.
- 突出目前的研究趋势和未来在避障机器人领域的前景.
主要方法:
- 复习经典的避障算法 (例如,Bug算法,Dijkstra的算法).
- 探索包括遗传算法和基于神经网络的方法在内的现代方法.
- 对预测方法和深度学习策略进行分析,以提高障碍回避能力.
主要成果:
- 详细比较不同避障算法的优缺点.
- 为每个算法方法确定合适的应用领域.
- 洞察障碍回避技术的演变和当前最先进的技术.
结论:
- 避免障碍的算法对推进机器人和自主系统至关重要.
- 在深度学习和预测方法等领域的持续研究有望提供更强大的导航解决方案.
- 选择合适的算法取决于特定的应用要求和环境复杂性.
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