Abstract
This paper discusses the mapping of ionizing radiation on building surfaces by using an unmanned aircraft system (UAS). The mapping task itself is important for the decommissioning of various nuclear facilities, for example, fuel processing sites or nuclear waste storage areas. The surface map can inform relevant authorities about the strength and distribution of radioactive sources inside an investigated building. The UAS is employed for the given purpose thanks to its many advantages, such as low price and the possibility of approaching a surface closely; moreover, the applied technique enables the user to create a 3D model of the target via such means as aerial photogrammetry. We set up an approximate model of a real building within our university campus, capturing the inner structures and subdividing the examined area into partial sectors, or groups, according to the construction materials; this criterion is relevant for simulating radiation propagation. The choice of the actual study location allows future experimental verification of the proposed methods; moreover, we can work with authentic photogrammetric products obtained during previous flights. In the project, two surface mapping methods are designed and tested on the simulated scenario, which assumes several radiation sources inside the building. One of the techniques simply assigns the measured value to the nearest point of the photogrammetric building model, while the other considers also rough information on the position of the sources to estimate the surface intensity more precisely. For better interpretation, the scattered data points are interpolated. Finally, the results of both approaches are compared with the computed reference map.
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Acknowledgments
This work was supported by the European Regional Development Fund under the project Robotics 4 Industry 4.0 (reg. no. CZ.02.1.01/0.0/0.0/15_003/0000470).
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Lazna, T., Gabrlik, P., Jilek, T., Burian, F. (2020). Simulating UAS-Based Radiation Mapping on a Building Surface. In: Mazal, J., Fagiolini, A., Vasik, P. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2019. Lecture Notes in Computer Science(), vol 11995. Springer, Cham. https://doi.org/10.1007/978-3-030-43890-6_11
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