Terrestrial laser scanning enables accurate capture of complex spaces, such as the interior of factories, hospitals, process plants, and civil infrastructure. Reconstruction of 3D shape and appearance from unmanned aerial vehicle (UAV)-based photographs enables operators to rapidly capture exterior structures and their surroundings. Merging these technologies helps users quickly and accurately capture their entire facility—including impractical areas such as rooftops—and provide outdoor context to indoor scans for complete site mapping. We will present workflows for combining terrestrial scan data and UAV photo models into a unified point cloud for visualization, interrogation, design, modeling, and analysis. We will highlight how operators can capitalize on the accuracy and reliability of laser scanning through UAVs’ capability to quickly capture expansive environments in great detail, and provide reality-captured context to improve downstream workflows in AutoCAD software, Revit software, and InfraWorks software. This session features ReCap 360. AIA Approved
- Learn how to align registered, terrestrial laser scans with scaled and aligned photo point clouds using survey control
- Learn how to create scaled and aligned photo point clouds using organic control points from laser scans
- Learn best practices for the collection of laser scan and UAV photos for efficiently creating high-quality interior and exterior point clouds of large industrial and commercial spaces
- Learn about workflows for preparing point clouds for use in design tools such as AutoCAD, Revit, and InfraWorks
Marc Zinck is a principal engineer at Autodesk, Inc., in the AutoCAD ReCap Group and the technical lead for ReCap Fly, Autodesk’s unmanned aerial systems (UAV) initiative, where he works on the collection, processing, analysis, and visualization of captured sensor data. Prior to joining Autodesk, Zinck designed, developed, and commercialized automated reality-capture systems for laser-scan workflows. Earlier in his career as a researcher at the Carnegie Mellon Robotics Institute, Zinck worked on sponsored research projects for the Defense Advanced Research Projects Agency (DARPA), ARL, and National Aeronautics and Space Administration (NASA) building laser-based robot navigation and mapping systems for ground and air vehicles. He holds a degree in computer science from Carnegie Mellon School of Computer Science, has co-authored several peer-reviewed publications, and is an inventor on patents for geometry synthesis and automated point-cloud collection. Zinck presents regularly on the topics of terrestrial laser scanning, UAV photo capture, and other reality-computing technologies.