一种显式几何特征匹配的激光雷达SLAM方法

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关键词：同时定位与建图；激光雷达里程计；特征提取；非线性优化中图分类号：TP242.6DOI：10.3969/j.issn.1004-132X.2025.08.017 开放科学（资源服务）标识码（OSID）：

Abstract：Currently，most LiDAR-SLAM systems utilized front-end odometry to estimate the initial pose and back-end optimization to refine the pose，but they lacked batch back-end optimization approaches. To address these issues， a comprehensive LiDAR-SLAM system was proposed based on explicit geometric features.This system employed agglomerative hierarchical clustering for plane feature point cloud segmentation and employed local curvature computation to filter linear feature points. Furthermore，the initial pose estimation of LiDAR motion was achieved through registering point cloud features and submap features. A local state optimization method was utilized based on linear and planar primitives， where linear and planar factors were merged within a factor graph model. By minimizing residuals between linear-to-linear and plane-to-plane associations， joint batch optimization of pose，linear，and planar parameters was achieved. Experimental results demonstrate that the proposed SLAM system achieves high precision localization and map construction in various scenarios，meeting real-time SLAM requirements.

Key words： simultaneous localization and mapping（SLAM）；LiDAR odometry； feature extraction; nonlinear optimization

0 引言

通常采用的同时定位与建图（simultaneouslocalizationand mapping，SLAM）技术按照传感器可划分为基于相机的视觉SLAM（visualSLAM，VSLAM）及基于激光雷达的LiDAR-SLAM。（剩余13090字）