3D reconstruction from images obtained by RGB-D camera provides a 3D model that reflects the current conditions of nuclear power plants (NPPs), and it is useful for field work support in NPPs. However, machinery equipment and pipes are intricately connected in NPPs and a lot of areas are not photographed because they are occluded by peripheral machines or pipes. It is feasible, but still challenging photographing those areas with RGB-D camera-mounted drones, due to the battery capability and the weight of drones. In this study, 3D reconstruction in cooperation with a light-weight mirror-mounted autonomous drone has been proposed and a novel method for determining drone’s flight path to scan those areas with a mirror has been developed. In this method, suitable locations for scanning the occluded areas with a mirror are detected and connected using multiple paths that are verified as safe to fly. The developed method was evaluated in the simulation environment. The results suggested that the developed method could obtain more points and photograph more occluded areas than the method of repeating random movements and the method to locally search for the optimal direction.