Mobile robot odometry estimates a robot’s position and orientation from measuring wheel
angle changes. Calibration of odometry involves estimating wheel radii and wheel
separation. This thesis devises novel odometry calibration methods that detect different floor
types in real time, and also models the effects of linear acceleration and path curvature to
significantly improve robot localisation and map accuracy. This involves novel floor
classification with colour and motor current sensors using a Support Vector Machine
algorithm. More accurate odometry models are proposed using data driven methods and
theoretic support from tyre mechanics.