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Simultaneous
Localisation and Mapping (SLAM) is
the problem of a robot being
autonomously able to build a map
of an unknown environment and
simultaneously localising itself
in the environment. This ability
makes a robot truly autonomous.
A considerable amount of research
has been carried out on SLAM using
vision sensors during last decade.
The aim of my thesis project is
first to study and compile a
survey of state-of-the-art visual
SLAM techniques. Then a dataset is
to be developed in order to enable
the implementation and evaluation
of different visual SLAM
techniques, and then a visual SLAM
technique is to be implemented on
the developed dataset in order for
the technique to be critically
evaluated.
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