A Path Planning Algorithm for UAV 3D Surface Inspection Based on Normal Vector Filtering and Integrated Viewpoint Evaluation

Abstract

The use of unmanned aerial vehicles (UAVs) for three-dimensional (3D) surface inspection has become an important tool in the field of large-scale structure maintenance. However, the commonly used UAVs inspection path planning (IPP) algorithms for 3D surface suffer from problems, such as path quality-dependent model accuracy, path inspection efficiency, and low inspection quality. To address these issues, this paper proposes a UAV 3D surface IPP algorithm based on normal vector filtering and integrated viewpoint evaluation (IVE). Generate a safe and effective set of viewpoints through uniform sampling and normal vector viewpoint filtering, and then use an IVE method combined with Monte Carlo tree search to select viewpoints, thereby generating a safe, efficient, and complete UAV surface inspection path. Simulation results show that the proposed method reduces path length by up to 72.5%, inspection time by up to 80.6%, planning time by up to 54.3%, and defective coverage ratio by up to 55.8% compared with existing algorithms. Real-world experiments on the sail sculpture and the Terracotta Warrior sculpture further illustrate the efficiency of the algorithm, successfully collecting high-quality surface data and validating its practical applicability for 3D structural inspections.