TL;DR
DZLoop is proposed, a novel LiDAR-based loop closure detection method that leverages multiple structural density images and Zernike moments that generates a robust global descriptor that effectively captures diverse structural characteristics of the environment.
Loop Closure Detection is a fundamental component of any SLAM system. By performing place recognition, a robot can correct accumulated drift errors arising from odometry uncertainties during the mapping process. Numerous techniques have been proposed in the literature to address this task under different sensor configu...
This paper proposes a loop closure detection method based on Key Plane Structures (KPS), which exploits the geometric stability of indoor plane structures to construct invariant global descriptors and provides more reliable loop closure constraints for pose graph optimization.
LiDAR-based place recognition is fundamental to loop closure and global localization in SLAM. Bird’s Eye View (BEV) projection has emerged as an effective paradigm for 3D point cloud processing, yet rotation robustness remains expensive: prior approaches either discretize SO(2) at <inline-formula><tex-math notation="La...
LiDAR localization and mapping play an important role in mobile robotics and autonomous driving systems, but points from dynamic objects in urban environments can be incorrectly associated with the local map during scan-to-map registration, introducing erroneous constraints into pose estimation and thereby degrading lo...
Loop closure detection plays a crucial role in LiDAR-based simultaneous localization and mapping (SLAM) by reducing accumulated drift and ensuring global map consistency. However, in substation inspection environments, repetitive equipment structures, complex ground conditions, and the limited discriminative capability...
A robust outdoor LiDAR SLAM framework that effectively combines ground constraints with a novel coarse-to-fine semantic loop closure detection method to resolve elevation drift and perceptual aliasing in complex environments is introduced.
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