Many conventional methods for map generation by mobile robots have tried to reconstruct a 3D geometric representation of the environment, which is time-consuming, error-prone and necessary to transform the map into the information available for the given task. This paper proposes a method to acquire a statistical map representation robust to sensor noise and directly usable for a navigation task. The robot is equipped with a ring of ultrasonic ranging sensors and a collision avoidance behavior is embedded in it. First, the mobile robot explores the environment in order to store a set of sequences of sonar data and principle component analysis is applied to reduce the dimensionality of the sonar data. As a result, each sequence of sonar data can be described as a score pattern of principal components. Next, these patterns are classified into typical local structures of the environment in order for the robot to discriminate them. Finally, a graph representation of the environment is constructed in which the...