Full Pitch Angular Three-dimensional (3-D) LiDAR Reconstruction Approach for Cramped Indoor Environments.

Current LiDAR systems are limited to vertical field of view (FoV) have a blind scanning region which leads to uncompleted three-dimensional (3-D) spatial reconstruction. To solve this problem this paper proposes a device mounted with a multi-layer LiDAR to collect data, which spins clockwise around the LiDAR's y-axis. Statistical outlier removal (SOR) and an optimized voxel-grid filter are employed to do the point cloud registration. The coarse registration and the fine registration are performed by 3-D normal distributions transform (NDT) and point-to-plane iterative closest point (ICP), respectively. The completed 3-D reconstruction is unrestricted by the LiDAR's vertical FoV. Additionally, the experimental results show that the proposed algorithm can improve the registration accuracy as measured by the value of the root mean square error (RMSE). [ABSTRACT FROM AUTHOR]