Public infrastructures such as bridges are common civil structures for road and railway transport. In Poland, many of the steel truss bridges were constructed in the 1950s or earlier. The aging managements and damage assessments are required to ensure safe operations of these old bridges. The first step of damage assessment is usually done via visual inspection. The said inspection procedure can be expensive, laborious and dangerous as it is often performed by trained personnel. As a solution to this, we have developed and used a custom-designed, modular aerial robot equipped with a CCD camera for the collection of high-resolution images. The images were merged into one single, high-resolution facade map that will be the basis for subsequent evaluation by bridge inspectors. It was observed that the collected images had encountered irregularities which decreases the reliability of the facade map. We have conducted experiments to estimate the correction of image perspective in terms of attitude and position of unmanned aerial vehicle (UAV). A Kriging model was utilized to parametrically model the aforementioned nonlinear relationship. The image reliability is then evaluated based on the variance of the parametric model. The generated information is further used for high fidelity automated image correction and stitching.

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