[Purposes] Point cloud data acquired by UAV-borne LiDAR systems are prone to contain void regions, leading to localized data gaps in the generated Digital Surface Model (DSM) and Digital Elevation Model (DEM). To reconstruct the missing terrain information, this paper proposes a void-completion method for UAV LiDAR point clouds that operates directly in the 3D point cloud space and incorporates local slope constraints. [Methods] The proposed method begins by identifying void boundaries