Comparing two sets of corresponding six degree of freedom data

This paper is concerned with comparing two sets of corresponding six degree of freedom data that consist of both object position and object orientation. Specifically, the best rotation and translation that aligns the position and orientation of one data set to the other is constructed by solving an optimization problem. In addition, a statistical method that identifies outliers in the data sets is proposed.

► Compared two sets of corresponding six degree of freedom (6DoF) data by creating the best homogeneous matrix (rotation and translation) that transforms one data set to the other.
► Created an error metric to analyze the 6DoF data.
► Formulated a statistical method to identify outliers in the 6DoF data.
► Compared with the absolute orientation problem and the hand-eye calibration problem on simulated and real 6DoF data.