Validating a 3D indoor radio propagation model that simulates the signal strength of a wireless device can be a challenging task\ndue to an incomplete or a faulty environment model. In this paper, we present a novel method to simulate a complete indoor\nenvironment that can be used for evaluating a radio propagation model efficiently. In order to obtain a realistic and robust model\nof the full environment, the OctoMap framework is applied.The system combines the result of a SLAM algorithm and secondly a\nsimple initialmodel of the same environment in a probabilistic way. Due to this approach, sensor noise and accumulated registration\nerrors are minimised. Furthermore, in this article, we evaluate the merging approach with two SLAM algorithms, three vision\nsensors, and four datasets, of which one is publicly available. As a result, we have created a complete volumetric model by merging\nan initial model of the environment with the result of RGB-D SLAM based on real sensor measurements.
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