AbstractCivil infrastructure systems, such as harbors and airports, support transportation between international communities. Inspection of facilities in a large area is labor-intensive and time-consuming work, and the result can sometimes be inaccurate due to humans’ limitations and inexperience. In this study, an autonomous aerial platform with a functional multipoint patrol module is developed to acquire images of inspected targets. It integrates a high-definition digital surface model (DSM) and a route-searching algorithm to optimize flying route planning. The collected unmanned aerial vehicle (UAV) images are then subjected to a matching technique that automatically detects exposure positions and corrects image distortions. Finally, target facilities are extracted from multitemporal images using object detection techniques so that the status of the inspected targets can be tracked and evaluated. Case studies in real-world settings have been conducted. As this proposed approach refines the efficiency and reliability of the facility inspection task, significant improvements are expected to deal with wide area monitoring and flexibility management.

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