Global localization in maps is an important Problem in the field of autonomous robotics and is required for many indoor and outdoor tasks in this domain. The Monte-Carlo-Localization solves this problem by considering a set of pose hypotheses in the environment. While this method has been well studied in the two-dimensional case, global localization in three-dimensional map representations of mobile robotic systems with six degrees of freedom has been neglected in terms of performance.