基于视觉数据分析与优化的无人机自动化结构检测路径规划
UAS-based Automated Structural Inspection Path Planning via Visual Data Analytics and Optimization
AI总结：
针对无人机基础设施检测中的路径规划问题，提出以覆盖为约束、路径最短为目标的两阶段算法（遗传算法定视点、贪心算法定姿态），经敏感性分析和实例验证，兼顾效率与检测质量。
摘要：
无人机系统（UAS）在基础设施检测中的应用已获得显著关注。然而，考虑到基础设施的巨大规模和复杂性质，自动化对于提高检测作业的效率和质量的至关重要。这方面的核心问题之一是选择一条最优的自动化飞行路径，该路径能够在最小化飞行时间的同时实现任务目标。本文提出了一种在结构检测背景下路径规划问题的有效公式化表述。覆盖范围作为约束条件以保证损伤可检测性，路径长度作为目标被最小化，从而在确保检测质量的同时最大化效率。随后设计了一种两阶段算法来解决路径规划问题，该算法由用于确定视点位置的遗传算法和用于计算姿态的贪心算法组成。进行了全面的敏感性分析，以证明所提出算法的有效性和适用范围。还展示了算法的应用实例，包括具有禁飞区的部分空间检测和聚焦检测，证明了所提出方法满足实际结构检测需求的灵活性。总之，本研究的结果凸显了所提出方法的可行性，并为将自动化融入基于UAS的结构检测任务规划奠定了基础。
英文摘要：
Unmanned Aerial Systems (UAS) have gained significant traction for their application in infrastructure inspections. However, considering the enormous scale and complex nature of infrastructure, automation is essential for improving the efficiency and quality of inspection operations. One of the core problems in this regard is electing an optimal automated flight path that can achieve the mission objectives while minimizing flight time. This paper presents an effective formulation for the path planning problem in the context of structural inspections. Coverage is guaranteed as a constraint to ensure damage detectability and path length is minimized as an objective, thus maximizing efficiency while ensuring inspection quality. A two-stage algorithm is then devised to solve the path planning problem, composed of a genetic algorithm for determining the positions of viewpoints and a greedy algorithm for calculating the poses. A comprehensive sensitivity analysis is conducted to demonstrate the proposed algorithm's effectiveness and range of applicability. Applied examples of the algorithm, including partial space inspection with no-fly zones and focused inspection, are also presented, demonstrating the flexibility of the proposed method to meet real-world structural inspection requirements. In conclusion, the results of this study highlight the feasibility of the proposed approach and establish the groundwork for incorporating automation into UAS-based structural inspection mission planning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
