Abstract
Over the past decades, several bridges have collapsed causing many losses. To keep bridges in a fully functional condition, a good maintenance system should be implemented. Although several new techniques have been developed and used recently to detect bridge defects, annual visual inspection remains the main approach for detecting surface defects, such as cracks. An Unmanned Aerial Vehicle (UAV), equipped with Light Detection and Ranging (LiDAR) scanner, can fly to reach all parts of a large structure. This equipment is capable of scanning the inaccessible surfaces of the bridges at a closer distance, which improves safety, accuracy, and efficiency. Using his method in structural inspection is attracting attention in research, and recent advancements have been made to automate and optimize the path planning of the UAV. However, the difference between the criticality levels of sections is not reflected in these methods. This paper proposes a path planning method of LiDAR-equipped UAV for bridge inspection using Genetic Algorithm (GA) and A* to solve Traveling Salesman Problem (TSP) considering the potential locations of surface defects such as cracks. The objective is minimizing time-of-flight to achieve acceptable visibility.
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Bolourian, N., Hammad, A. (2019). Path Planning of LiDAR-Equipped UAV for Bridge Inspection Considering Potential Locations of Defects. In: Mutis, I., Hartmann, T. (eds) Advances in Informatics and Computing in Civil and Construction Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-00220-6_65
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DOI: https://doi.org/10.1007/978-3-030-00220-6_65
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