Introduces a sensor-agnostic loop closure pipeline for LiDAR SLAM using density maps, ground alignment, ORB on BEV projections, BST retrieval, and pruning to handle perceptual aliasing.
Carlevaris-Bianco, A
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Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps
Introduces a sensor-agnostic loop closure pipeline for LiDAR SLAM using density maps, ground alignment, ORB on BEV projections, BST retrieval, and pruning to handle perceptual aliasing.