基于传感器融合的导航用于自主移动机器人.
Vygantas Ušinskis1, Michał Nowicki1, Andrius Dzedzickis1
1Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, LT-10105 Vilnius, Lithuania.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
本研究审查了用于机器人导航的传感器和人工智能,重点关注传感器融合和动态障碍复杂任务的路径规划. 它介绍了通道机器人导航的概念.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 传感器融合和导航系统
背景情况:
- 导航系统的快速进步遇到了越来越复杂的机器人任务.
- 挑战包括动态障碍,多机器人协调和在难以进入的环境中导航.
- 认知任务需要对象的评估超出了简单的检测,需要先进的AI.
研究的目的:
- 审查和比较用于移动机器人定位的传感器.
- 分析传感器与路径规划方法的集成.
- 评估传感器融合技术,并提出通道机器人导航的概念.
主要方法:
- 关于移动机器人定位传感器的综合文献综述.
- 对传感器组合进行比较分析,突出优缺点.
- 评估用于传感器数据处理和轨迹生成的人工智能 (AI) 方法.
主要成果:
- 在复杂的机器人导航中识别关键传感器及其局限性.
- 对传感器融合技术进行分析,以提高环境感知.
- 基于现有研究的道机器人导航新概念的介绍.
结论:
- 传感器融合和人工智能对于克服现代机器人导航挑战至关重要.
- 传感器和路径规划算法的有效集成对于强大的性能至关重要.
- 拟议的道机器人导航概念为复杂的环境提供了潜在的解决方案.
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