Automating Scan to BIM Operations Using Grasshopper

Abstract

Remote sensing technologies such as laser scanning and photogrammetry have advanced significantly in the field-to-BIM workflow in recent years, becoming key instruments for modeling as-built frameworks. They can be utilized to collect dense 3D measured data on the condition of a building, and the derived point cloud can be processed to generate the as-built BIM. It provides building information to report as-built conditions and serves as a skill set for data on problem-solving issues in civil engineering. This research presents an efficient and automated workflow for modifying and evaluating point cloud data, focusing on supporting scan-to-BIM operations. The workflow utilizes cubic voxel mesh creation and voxel subsampling techniques to ensure precise representation of scanned data. The validation of this reconstruction methodology using Grasshopper and Volvox demonstrates its potential to reduce manual labor and analysis typically required in conventional scan-to-BIM methodologies. The presented workflow simplifies the critical task of acquiring building profiles, an essential BIM result, and streamlines the overall process. The integration of the Volvox plugin has further augmented the capabilities of Grasshopper and Rhino, providing users with intuitive tools for manipulating point clouds. Automating certain operations through the presented workflow has significant potential to enhance the efficiency and accuracy of the scan-to-BIM methodologies. These findings have implications in architecture and design, demonstrating how technology can be leveraged to unlock new possibilities and streamline critical processes.