A fast, complete, point cloud based loop closure for LiDAR odometry and mapping

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This paper presents a loop closure method to correct the long-term drift in LiDAR odometry and mapping (LOAM).

• Our proposed method computes the 2D histogram of keyframes, a local map patch, and uses the normalized cross-correlation of the 2D histograms as the similarity metric between the current keyframe and those in the map.
• We show that this method is fast, invariant to rotation, and produces reliable and accurate loop detection.
• The proposed method is implemented with careful engineering and integrated into the LOAM algorithm, forming a complete and practical system ready to use.