Chemical Engineering Commons^™

Automated 3d Reconstruction Using Optimized View-Planning Algorithms For Iterative Development Of Structure-From-Motion Models, Samuel Arce, Cory Vernon, Joshua Hammond, Valerie Newell, Joseph Janson, Kevin Franke, John Hedengren

Faculty Publications

Unsupervised machine learning algorithms (clustering, genetic, and principal component analysis) automate Unmanned Aerial Vehicle (UAV) missions as well as the creation and refinement of iterative 3D photogrammetric models with a next best view (NBV) approach. The novel approach uses Structure-from-Motion (SfM) to achieve convergence to a specified orthomosaic resolution by identifying edges in the point cloud and planning cameras that “view” the holes identified by edges without requiring an initial model. This iterative UAV photogrammetric method successfully runs in various Microsoft AirSim environments. Simulated ground sampling distance (GSD) of models reaches as low as 3.4 cm per pixel, and generally, …