A Framework for Autonomous Inspection of Bridge Infrastructure using Uncrewed Aerial Vehicles

Traditional bridge inspections are labor-intensive, time-consuming, and costly, relying on human inspectors for close visual and physical examinations, making them subjective, inaccurate, and non-repetitive. Leveraging Uncrewed Aerial Vehicles (UAVs) for UAV-enabled bridge inspection (UBI) has the potential to save over 50% of costs compared to traditional methods. However, existing UBI research lacks a unified, end-to end autonomous solution, often presenting isolated automation solutions at each stage of the inspection process. In this work, a comprehensive framework for autonomous bridge inspection using a single UAV is presented, encompassing mission planning, data acquisition, data analysis, and decision-making. Bridges were chosen as the focus of the framework due to their mandated inspection requirements compared to other infrastructure assets. We define the UBI system architecture, evaluate specific methods for each system element, and finally present how the UBI can be achieved through a phased procedure. Using physical experiments, the proposed procedure is validated with low-cost off-the-shelf hardware and software components, which demonstrates not only the feasibility but also the simplicity of the proposed framework using currently available technology. This research offers a comprehensive solution to revolutionize bridge maintenance, improve safety, reduce expenses, and streamline the inspection process for the longevity of critical transportation infrastructure.