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在大型环境中使用3D LiDAR传感器的自主检查机器人的长期定位和映射系统

Wandeng Mao¹, Liang Jiang², Shanfeng Liu¹

¹State Grid Henan Electric Power Research Institute, Zhengzhou, Henan, China.

|July 31, 2025

概括

本研究介绍了一个基于3D LiDAR的系统,用于在关键环境中长期的机器人定位和地图维护. 该系统提高了准确性和稳定性,优于自主检查机器人的现有方法.

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:

具有3D LiDAR的移动机器人检查对于变电站至关重要,但在大型环境中面临局限性.
传统的LiDAR系统与传感器退化和动态对象作斗争,影响地图稳定性和机器人定位准确性.

研究的目的:

开发一个强大的基于3D LiDAR的系统,用于自主检查机器人的长期定位和地图维护.
为了克服规模,传感器退化和动态环境的挑战,实现可靠的机器人操作.

主要方法:

一个分层系统,包括SLAM (同时定位和映射) 子系统,全球定位子系统和地图维护子系统.
SLAM包括高效的局部地图表示,LiDAR测距,全球地图优化和使用行进立方体生成密集地图.
全球本地化使用新的ScanContext-ICP方法进行位置识别和姿势初始化,其次是代最接近点 (ICP) 进行改进.
地图维护跟踪环境变化,优先考虑稳定的特征,并通过时间和细分级别分析过不稳定的点.

主要成果:

与公开数据集上的最先进的LOAM方法相比,拟议的系统可以将平均绝对位置误差降低30%和38%.
显示出卓越的准确性和稳定性,在现实场景中获得高SLAM排名.
地图维护系统通过加权稳定特征和过动态元素,有效地提高了定位准确性.

结论:

开发的基于3D LiDAR的系统可为移动检查机器人提供有效的长期定位和地图维护.
该系统的提高准确性,稳定性和处理动态环境的能力使其适合在关键基础设施中自主部署.
层次化的SLAM,先进的全球本地化和智能地图维护的整合为机器人检查应用提供了重大进步.

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