In recent years, the advent of robust tracking systems has enabled behavioral analysis of individuals based on their trajectories. An analysis method based on a Point Distribution Model (PDM) is presented here. It is an unsupervised modeling of the trajectories in order to extract behavioral features. The applicability of this method has been demonstrated on trajectories of a realistically simulated mobile robot endowed with various controllers that lead to different patterns of motion. Results show that this analysis method is able to clearly classify controllers in the PDM-transformed space, an operation extremely difficult in the original space. The analysis also provides a link between the behaviors and trajectory differences.