Efficient low-collision UAV-based automated structural surface inspection using geometric digital twin and voxelized obstacle information

Abstract

The application of Unmanned Aerial Vehicle (UAV) automatic flight is increasingly popular for structural surface inspection. To address the low level of automation and insufficient adaption of the flight path in response to environmental obstacles, a method of automatic planning UAV inspection mission based on the Geometric Digital Twin (GDT) model and Voxelized Obstacle Information (VOI) is proposed. First, a method for shifting the Field of View (FOV) centroids in parallel is proposed to efficiently generate inspection waypoints. Second, a waypoints adjustment method based on environmental VOI of 3D point clouds is proposed to address the safety issues. Third, a method combining Genetic Algorithm (GA) with A* based on VOI is proposed for optimizing UAV flight path to avoid real-world obstacles. The feasibility of the proposed methods was verified in both an office building and a steel truss bridge. Compared to existing methods, the efficiency is significantly improved.