Abstract 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.

中文翻译：

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考虑潜在缺陷位置的配备 LiDAR 的无人机路径规划用于桥梁检查

摘要 传统的目视桥梁检查方法耗时且可能使检查人员处于危险境地。无人驾驶飞行器 (UAV) 最近被引入作为桥梁检查的有效工具。本文提出了一种使用配备有光探测和测距 (LiDAR) 扫描仪的无人机进行桥梁检查的 3D 路径规划方法。该方法结合遗传算法 (GA) 和 A* 算法来解决旅行商问题 (TSP)，考虑到桥梁表面缺陷（如裂缝）的潜在位置。目标是最大限度地减少飞行时间，同时实现最大的能见度。该方法提供了表面缺陷的潜在位置，以有效地实现对视点进行采样的垂直和重叠视图。计算与关键程度相关的可见性导致优先覆盖风险级别较高的区域。结果表明，根据区域的关键程度和所有视点的垂直视图考虑重叠视图，可以实现准确且省时的数据收集。