四足动物的自主导航使用覆盖路径规划与形态骨地图
Alexander James Becoy1,2, Kseniia Khomenko1, Luka Peternel1
1Department of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, Delft, Netherlands.
Frontiers in robotics and AI
|August 18, 2025
概括
这项研究引入了一种新的自主覆盖路径规划方法,使用2D地图骨架指导机器人. 该系统有效地导航和扫描环境,尽管面临地图漂移挑战,但实现了86.5%的途径点可达性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 计算机科学 计算机科学
背景情况:
- 自主机器人需要有效的覆盖路径规划,用于环境扫描.
- 同时定位和映射 (SLAM) 提供了对机器人操作至关重要的二维导航地图.
- 在非结构化环境中路径规划带来了重大的计算挑战.
研究的目的:
- 提出一种用于在非结构化环境中自主覆盖路径规划的新方法.
- 通过利用二维导航图的形态骨架来生成最佳路径.
- 通过有限状态机器 (FSM) 控制来增强机器人导航和扫描能力.
主要方法:
- 从2D地图的形态骨架生成一个兴趣点 (POI) 的序列.
- 命令POI根据机器人的当前位置创建最佳路径.
- 使用有限状态机器 (FSM) 来管理导航 (Nav2) 和本地扫描模式.
主要成果:
- 该方法展示了高效的地图处理,地图阅读和路径规划计算需要几毫秒.
- 该系统在受控的室内环境中在五次试验中实现了86.5%的途径点可达性.
- 发现地图处理的计算时间分别为地图阅读器和路径规划器的22.0 ns/pixel和8.17 μs/pixel.
结论:
- 建议的覆盖路径规划方法对于自主环境扫描是有效的.
- 该系统在经过测试的场景中表现出良好的时间效率和途径点可达性.
- 2D导航地图中的地图漂移仍然是一个限制,需要进一步调查.
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