A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing

In order to investigate the use of unmanned aerial vehicles (UAVs) for future application in road damage detection and provide a theoretical technical basis UAV detection, this paper determined recommended flight camera parameters based on needs continuous image capture pavement disease recognition. Furthermore, realize automatic route planning control, photography stitching smoothing tasks, control framework Dijkstra algorithm, speeded-up robust features (SURF) random sampling consistency (RANSAC) gradual out weight fusion method, was also proposed paper. With Canny operator, it verified that stitched long obtained by method is applicable machine learning identification.