This study presents an improved UAV-based structure inspection method that integrates advanced 3D modeling and optimized path planning with obstacle avoidance. The system uses Meshroom, an open-source software, to combine multiple sets of 3D point clouds collected by a UAV-mounted 3D camera into a complete 3D model of the structure. Because point cloud data typically contain an overwhelming number of points, they are grouped into smaller sets, each represented by an oriented bounding box (OBB). This step significantly reduces the complexity in path-planning calculations. The UAV, modeled as a flying sphere, initially moves along a straight path from its starting point to a target position. A gradient-based optimization method then adjusts this trajectory to maintain a safe distance between the UAV and the OBBs representing the obstacles. Results show that the proposed method successfully generates safe and efficient UAV flight paths, improving both the accuracy and safety of UAV-based structure inspections.