  Determining the position and orientation of a sensor vis-a-vis its
surrounding, while simultaneously mapping the environment around that sensor or
simultaneous localization and mapping is quickly becoming an important
advancement in embedded vision with a large number of different possible
applications. This paper presents a comprehensive comparison of the latest
open-source SLAM algorithms with the main focus being their performance in
different environmental surroundings. The chosen algorithms are evaluated on
common publicly available datasets and the results reasoned with respect to the
datasets' environment. This is the first stage of our main target of testing
the methods in off-road scenarios.
