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The navigation system is based on our previous works, primarily on the approach presented in \cite{ebner-15}.
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For this, we have been awarded the best overall paper award at IPIN 2015 in Banff, Canada.
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Since then, we extended our approach by prior navigation knowledge using realistic human walking paths \cite{} and smoothing methods \cite{}.
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Additionally, a self-developed map editor allows for creating advanced 3D maps and realistically shaped stairs.
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Compared to many other systems, we avoid any time-consuming fingerprinting and calibration processes and are able to start with a uniform distribution over the whole building.
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All calculations are computed in real time on a commercial smartphone, in most of our examples this is the Motorola Nexus 6.
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The system is implemented in C++ using the Qt framework and OpenCL.
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An overview of all involved components and the sensor fusion procedure can be seen in fig. \ref{}.
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Here, the smartphone provides all necessary measurements and no additional device is needed.
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This ensures sensor is defect or is not provided by the smartphone itself
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\begin{itemize}
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\item Hinfuehren zum System
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