A method is presented for automated localization of a laser scanner in indoor environments by matching planar features extracted from range data. Plane correspondences are used in a linear least-squares adjustment model to estimate the relative scanner positions in consecutive scans. The performance of the method is demonstrated using two datasets of building interiors. Accuracy assessment of the computed positions shows localization errors of a few centimeters.
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Kourosh Khoshelham (2010) studied this question.
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