LAUSR

Abstract 3D laser scanning is a widely adopted technique to capture the conditions of existing buildings for as-is BIM reconstruction. The quality of the scan data directly affects the quality of the reconstructed BIM models. Thus, it is necessary to conduct scan planning before data acquisition to determine the optimal scan positions and parameters that satisfy the required data quality and minimize the data collection time. However, most of the previously developed scan planning methods are based on accurate prior information (such as 2D drawings and 3D models) of the building, which contradicts with the fact that the 2D or 3D information of existing buildings is usually out-of-date or absent. To fill this gap, this study aims to develop a scan planning method for existing buildings without BIM based on user-defined data quality requirements and the genetic algorithm (GA). The proposed method firstly conducts a pre-scanning to quickly capture a preliminary point cloud of the building and then segments the point cloud into planar segments. Secondly, a user-friendly graphical user interface (GUI) is provided for the user to define customized point cloud data quality requirements based on the planar segments. Lastly, the GA is adopted to find out the optimal scan positions and parameters that satisfy the user-defined data quality requirements and achieve the minimal total scanning time. Validation experiments were conducted on two scenes and demonstrated that the proposed method had advantages of higher time efficiency, higher data completeness, and lower data redundancy compared to the manual scan planning method.