LiDAR-equipped UAV path planning considering potential locations of defects for bridge inspection

Conventional visual bridge inspection methods are time consuming and may put the inspector in dangerous situations. Unmanned Aerial Vehicles (UAVs) have been recently introduced as an effective tool for bridge inspection. This paper proposes a 3D path planning method for using a UAV equipped with a Light Detection and Ranging (LiDAR) scanner for bridge inspection. The method integrates a Genetic Algorithm (GA) and A* algorithm to solve the Traveling Salesman Problem (TSP) considering the potential locations of bridge surface defects such as cracks. The objective is minimizing time of flight while achieving maximum visibility. The method provides the potential locations of surface defects to efficiently achieve perpendicular and overlapping views for sampling the viewpoints. Calculating the visibility with respect to the level of criticality leads to giving the priority to covering the areas with higher risk levels. The results reveal that considering overlapping views based on the level of criticality of the zones and perpendicular view for all viewpoints result in accurate and time-efficient data collection.