Abstract: When creating dense point cloud maps for large-scale scenes, it's difficult for current 3D measurement systems to balance their measurement range and point cloud density. Therefore, a swinging single-layer LiDAR based dense point cloud map reconstruction system for large-scale scenes is designed. Firstly, the stable and accurate omnidirectional swing of a large LiDAR is realized. Then, the point cloud concatenation method at a single measuring point and the registration method at multiple measuring points are given. Finally, a density analysis method for projected 3D point cloud is proposed, and the simulation results are compared and evaluated. Experimental results show that the effective measurement distance of the system exceeds 75 m, the measurement range covers ±45° pitching angle, the point cloud spacing is less than 20 cm, and the point cloud distribution is uniform. Meanwhile, the view field and point cloud distribution of the device can be adjusted, and a larger scene can be reconstructed by point cloud registration at multiple measuring points.