Increasing robustness in self-localization and pose estimation

Ideally, an algorithm used for either self localization or pose estimation would be both efficient and robust. Many researchers have based their techniques on the absolute orientation research of B. K. P. Horn. As will be shown in this paper while Horn's method performs well with an additive Gaussian noise of large variance, mismatches and outliers have a move profound effect. In this paper the authors develop a new closed-form solution to the absolute orientation problem, featuring techniques specifically designed for increasing the robustness during the critical rotation determination stage. We also include a comparative analysis of the various strengths and weaknesses of both Horn's and the new techniques.