Currently, bridge inspections mainly employ inspection vehicles and directed drone inspections, which present issues such as inspection gaps and imbalanced monitoring areas. For the inspection requirements of different key components of bridges and, based on the symmetric structure of sparse bridge point clouds, was a UAV path-planning algorithm driven by structural mapping of sparse bridge point clouds was proposed. Firstly, utilizing the bridge point cloud model, a point cloud completion algorithm leveraging structural symmetry was designed to achieve the completion of missing parts of the bridge model. Secondly, the Sanjiang Bridge was divided into the pier and the main girder, and feature points were extracted for each module to obtain the relative positions of the bridge components and to determine the inspection range. Finally, according to photogrammetry and inspection task requirements, optimal waypoints were interpolated and expanded between the feature points, and all waypoints were connected to generate a feasible flight path. An overall coverage rate of 91.3% for Sanjiang Bridge is achieved, which is about 9.4% higher than the A* algorithm, improving the efficiency of bridge monitoring and strongly supporting refined bridge detection. This method effectively reduces the existing loopholes in bridge detection and provides a convenient and efficient new idea for unmanned aerial vehicle bridge inspection route planning.