Different practical applications have emerged in the last few years, requiring periodic and detailed inspections to verify possible structural changes. Inspections using Unmanned Aerial Vehicles (UAVs) should minimize flight time due to battery time restrictions and identify the terrain’s topographic features. In this sense, Coverage Path Planning (CPP) aims at finding the best path to coverage of a determined area respecting the operation’s restrictions. Photometric information from the terrain is used to create routes or even refine paths already created. Therefore, this research’s main contribution is developing a methodology that uses a metaheuristic algorithm based on point cloud data to inspect slope and dams structures. The technique was applied in a simulated and real scenario to verify its effectiveness. The results showed an increasing 3D reconstructions’ quality observing optimizing photometric and mission time criteria.

中文翻译：

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基于点云的结构检查覆盖路径规划优化框架

最近几年出现了各种实际应用，需要定期和详细的检查以验证可能的结构变化。由于电池时间的限制，使用无人飞行器（UAV）进行的检查应将飞行时间减至最少，并确定地形的地形特征。从这个意义上讲，覆盖路径规划（CPP）的目的是在遵守操作限制的情况下找到确定区域的最佳覆盖路径。来自地形的光度信息用于创建路线，甚至优化已经创建的路径。因此，这项研究的主要贡献是开发了一种方法，该方法使用基于点云数据的元启发式算法来检查边坡和大坝结构。将该技术应用于模拟和真实场景以验证其有效性。