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一个实时语义地图生产系统用于室内机器人导航

Raghad Alqobali¹, Reem Alnasser², Asrar Rashidi²

¹Saudi Data and AI Authority, Riyadh 12382, Saudi Arabia.

Sensors (Basel, Switzerland)

|October 26, 2024

概括

本研究介绍了移动机器人的语义地图制作系统,增强室内导航. 该系统使用LiDAR和视觉,实现了高级自动任务的78.86%的地图构造精度.

科学领域:

机器人技术机器人技术机器人技术
计算机视觉计算机视觉
人工智能的人工智能

背景情况:

传统的网格地图缺乏对高级机器人任务至关重要的语义信息.
提高室内导航需要更丰富的环境理解超越几何数据.

研究的目的:

为移动机器人室内导航开发一个语义地图制作系统.
整合LiDAR和基于视觉的系统,用于丰富的语义地图生成.
通过使用低成本硬件和ROS验证系统的效率和可访问性.

主要方法:

采用LiDAR技术和基于视觉的数据采集系统.
使用了You Only Look Once (YOLO) v3对象检测模型来提取语义信息.
在室内环境中的模拟实验中使用机器人操作系统 (ROS) 验证了系统.

主要成果:

实现了高效的对象识别准确度和对象定位.
在语义地图制作中证明了高精度.
实现了78.86%的平均地图构造准确度.

结论:

拟议的系统有效地产生语义地图,用于增强室内机器人导航.
低成本硬件和YOLO v3的整合使得系统可访问和高效.
该系统通过提供丰富的环境背景,促进了先进的自主任务.

关键词:

路径规划路径规划路径规划机器人导航机器人导航机器人视觉机器人视觉机器人视觉语义地图是一个语义地图.

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