| Abstract: |  The Random Finite Set approach to Bayesian Simultaneous Localization and Mapping (SLAM)
is a new method which provides promising results at least in the presence of clutter measurements.
The goal of this thesis is to implement and experimentally verify the Random Finite Set Multi Vehicle SLAM in 3D.
Both, simulated and real life datasets are evaluated to provide complete performance and
precision analysis of the proposed implementation.
Moreover, the collected dataset is publicly available as well as implemented library for the
Random Finite Set Filtering as well as library in a form of standalone C++ library wrapped into the Robot Operating
System package.
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