Multi-Layer Coverage Path Planner for Autonomous Structural Inspection of High-Rise Structures

In this paper, a novel 3D coverage path planning method, which is efficient and practical for inspection of high-rise structures such as buildings or towers, using an unmanned aerial vehicle (UAV) is presented. Our approach basically focuses on developing a model-based path planner for structural inspection with a prior map, which is opposite to a non-model based exploration. The proposed method uses a volumetric map which is made before the path planning. With the map, the whole structure is divided into several layers for efficient path planning. Firstly, in each layer, a set of the normal vectors of the center point of every voxel is calculated, and then the opposing vectors become viewpoints. Due to too many viewpoints and an overlapped inspection surface, we down-sample them with a voxel grid filter. Then, the shortest tour connecting the reduced viewpoints must be computed with the Traveling Salesman Problem (TSP) solver. Lastly, all the paths in each layer are combined to form the complete path. The results are verified using simulations with a rotary wing UAV and compared with other state-of-the-art algorithm. It is proven that our method performs much better for structural inspection with respect to computation time as well as the coverage completeness.