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通过平面优化和平面SLAM在LiDAR扫描中检测和利用反射

Yinjie Li¹, Xiting Zhao¹, Sören Schwertfeger¹

¹Key Laboratory of Intelligent Perception and Human-Machine Collaboration, ShanghaiTech University, Ministry of Education, Shanghai 201210, China.

Sensors (Basel, Switzerland)

|August 10, 2024

概括

在LiDAR传感器中,反射表面会导致数据错误. 这项研究优化了反射平面映射,以提高机器人和3D重建中的分类准确性,增强本地化和导航.

科学领域:

机器人和传感器融合技术
计算机视觉计算机视觉
3D重建的3D重建

背景情况:

在LiDAR传感器中,玻璃和镜子等材料的反射会导致不一致的数据.
这些不一致性给机器人定位,绘图和导航带来了重大挑战.
现有的方法很难准确地解释反射表面.

研究的目的:

开发一种可靠的方法来识别和绘制LiDAR数据中的反射平面.
通过减轻反射引起的错误来提高基于LiDAR的定位和绘图的准确性.
提高 LiDAR 探测在具有反射表面的复杂环境中的适用性.

主要方法:

通过在多个LiDAR扫描中改进平面检测参数,构建一个全局,优化的反射平面地图.
将反射平面估计集成到平面SLAM (同时定位和映射) 算法中.
基于优化的反射平面地图对LiDAR读数进行分类.

主要成果:

与单次扫描方法相比,拟议的方法在LiDAR读数中实现了更高的分类准确性.
在SLAM框架内证明了反射平面映射技术的实用性.
实验验证证了对处理反射环境的显著改进.

结论:

对反射平面的优化映射有效地解决了LiDAR传感中的数据不一致问题.
开发的方法提高了机器人定位,绘图和导航在具有反射表面的环境中的可靠性.
开源代码和数据为可重复性和进一步研究提供.

关键词:

斯拉姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯平面优化平面优化反射检测反射检测的检测

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