Paper and the corresponding source code for LiDAR SLAM
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<<Real-Time Loop Closure in 2D LIDAR SLAM>> , ICRA 2016 <<Efficient Sparse Pose Adjustment for 2D Mapping>> (SPA) <>(BBS)
Google Cartographer implementation to them. Github: https://github.com/googlecartographer/cartographer
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<<SegMatch Segment based on loop-closure 3D point clouds>> 2017 <<SegMap 3D Segment Mapping using Data-Driven Descriptors>> 2018
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<<Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments>>(201806) <>(2017_11)
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<>2017
<<LOAM: LiDAR Odometry and Mapping in Real-Time>> 2014 -
<<Joint Self-Localization and Tracking of Generic Objects in 3D Range Data>> <<Interlacing Self-Localization,Moving Object Tracking and Mapping for 3D Range Sensors>>
Tracking Moving Object: https://github.com/FrankMoosmann/FranksVelodyneAlgos
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Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications
Fast 3D Segmentation: https://github.com/VincentCheungM/Run_based_segmentation (Some innovation not implemented!)