| Abstract: |  In this work we describe an improvement of a state of the art monocular vision-based navigation system called SURFNav.
The system, which is based on the map and replay technique, relies on feature detection, description and matching algorithms.
We evaluate the impact of various feature extraction algorithms on navigation quality.
Moreover we discuss methods, which can increase the amount of usefull information in the already created maps.
We also introduce a method, which can evaluate the quality of the given map for navigation.
By combination of the aforementioned methods, we have achieved greater robustness of the SURFNav navigation system.
A large dataset, which was necessary to create to achieve our goals is also described.
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