This paper presents a new trajectory planning algorithm for three-dimensional autonomous UAV volume coverage and visual inspection. The algorithm is an extension of a state-of-the-art Heat Equation Driven Area Coverage (HEDAC) multi-agent area coverage algorithm for three-dimensional domains. Given a target coverage density field, the algorithm designs a potential field to minimize the remaining density and generate trajectories using potential gradients to direct UAVs to the regions with higher potential. Collisions between agents and agents with domain boundaries are prevented by implementing the distance field and correcting the agent's direction vector when the distance threshold is reached. For visual inspection applications, the algorithm is supplemented with the camera direction control. A field containing the distance from any point in the domain to the structure surface is designed. The gradient of the distance field is calculated to obtain the camera orientation throughout the trajectory. Three different test cases of varying complexities are considered to validate the proposed method for visual inspection. The simplest scenario is a synthetic portal-like structure inspected using three UAVs. The other two inspection scenarios are based on realistic structures where UAVs are commonly used: a wind turbine and a bridge. In the inspection of a wind turbine, two simulated UAVs traversing rather smooth spiral trajectories successfully explore the entire turbine structure. The bridge test case demonstrates effective visual inspection of the complex structure and srves for comparison with the state-of-the-art in trajectory planning where the HEDAC algorithm allowed more surface area to be inspected under the same conditions. The limitations of the method are analyzed, focusing on computational efficiency and adequacy of spatial coverage to approximate the surface coverage.
翻译:本文为三维自主UAV体积覆盖和视觉检查提供了一个新的轨迹规划算法。 算法是三维域的最新热赤道驱动区域覆盖多试剂区域覆盖算法的延伸。 鉴于一个目标覆盖密度字段, 算法设计了一个潜在的字段, 以将剩余密度最小化并生成轨迹, 使用潜在的梯度将UAV引导到潜力较高的区域。 具有域界的代理商和代理商之间的碰撞通过实施距离字段和在距离阈值达到时纠正代理商的方向矢量来防止。 对于视觉检查应用程序, 算法与摄像头方向控制相补充。 一个包含从域任何地点到结构表面距离的字段。 计算距离字段的梯度是为了在整个轨道上获得摄取的相机方向。 考虑三个不同的测试案例来验证拟议的视觉检查方法。 最简单的假设是使用3个UAVAVS来进行合成的门户式结构检查。 另外两种检查假设情景是以现实的结构为基础, 通常使用UAVAVS的逻辑值: 风轮机机机和直径直径直径直径直径直路路路路路路路路路路路路路结构的对比。 在测试中, 测试中, 测试中, 直径直径直路路路路路路路路路路路路路路路路路路路路路路路路路路段结构的直路路路段结构的校路路路路路路路路路路路路路路路路路路路路路路路路路路路路段结构。