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Loop-closure detection, also known as place recognition, aiming to identifypreviously visited locations, is an essential component of a SLAM system.Existing research on lidar-based loop closure heavily relies on dense pointcloud and 360 FOV lidars. This paper proposes an out-of-the-box NDT (NormalDistribution Transform) based global descriptor, NDT-Map-Code, designed forboth on-road driving and underground valet parking scenarios. NDT-Map-Code canbe directly extracted from the NDT map without the need for a dense pointcloud, resulting in excellent scalability and low maintenance cost. The NDTrepresentation is leveraged to identify representative patterns, which arefurther encoded according to their spatial location (bearing, range, andheight). Experimental results on the NIO underground parking lot dataset andthe KITTI dataset demonstrate that our method achieves significantly betterperformance compared to the state-of-the-art.

NDT-Map-Code: A 3D global descriptor for real-time loop closure detection in lidar SLAM