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Efficient low-collision UAV-based automated structural surface inspection using geometric digital twin and voxelized obstacle information
Automation in Construction ( IF 9.6 ) Pub Date : 2025-01-13 , DOI: 10.1016/j.autcon.2025.105972
Yonghui An, Jianren Ning, Chuanchuan Hou, Jinping Ou

The application of Unmanned Aerial Vehicle (UAV) automatic flight is increasingly popular for structural surface inspection. To address the low level of automation and insufficient adaption of the flight path in response to environmental obstacles, a method of automatic planning UAV inspection mission based on the Geometric Digital Twin (GDT) model and Voxelized Obstacle Information (VOI) is proposed. First, a method for shifting the Field of View (FOV) centroids in parallel is proposed to efficiently generate inspection waypoints. Second, a waypoints adjustment method based on environmental VOI of 3D point clouds is proposed to address the safety issues. Third, a method combining Genetic Algorithm (GA) with A* based on VOI is proposed for optimizing UAV flight path to avoid real-world obstacles. The feasibility of the proposed methods was verified in both an office building and a steel truss bridge. Compared to existing methods, the efficiency is significantly improved.

中文翻译:


使用几何数字孪生和体素化障碍物信息,基于无人机的高效低碰撞自动结构表面检测



无人机 (UAV) 自动飞行的应用在结构表面检测中越来越受欢迎。针对响应环境障碍物的自动化水平低、飞行路径适应性不足的问题,该文提出一种基于几何数字孪生(GDT)模型和体素化障碍物信息(VOI)的无人机自动规划巡检任务方法。首先,提出了一种并行移动视场 (FOV) 质心的方法,以有效地生成检查航路点。其次,针对安全问题,提出了一种基于三维点云环境VOI的航点平差方法。再次,提出了一种基于 VOI 的遗传算法 (GA) 与 A* 相结合的方法,用于优化无人机飞行路径以避开现实世界的障碍物。所提出的方法的可行性在办公楼和钢桁架桥中都得到了验证。与现有方法相比,效率显著提高。
更新日期:2025-01-13
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