The effect of changes in the environment on the performance of a SLAM algorithm
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2022-01-30
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en
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Abstract
In this thesis the effects of three variables on the results of a SLAM algorithm
were analyzed. The manipulated variables are: added noise to the distance
and motion sensor and slipperiness of the wheels. The aim of this thesis is to
find out how these variables affect SLAM maps and if any structure can be
found in the effects. This thesis proposes that a mapping can be learned by
a Neural Network that would optimize SLAM maps by removing the effects.
The research found that there is an effect on the maps for added noise to
the distance and motion sensor of a robot. A structure in the effects was
only identified for the noisy distance sensor variable.
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Faculteit der Sociale Wetenschappen