This paper presents a contribution on the navigation of autonomous mobile vehicles in structured indoor environments, where most of the objects are made by perpendicular sides to the floor. We propose a navigation algorithm with the intention of bringing down the environment recognition problem, and, in this way, it allows the mobile robot to readjust its path dynamically. We propose to use some patterns made of a set of laser beam planes suitably faced. The light pattern, that is projected by the mobile robot on the navigation environment, generates images that allow it to identify walls, doors, and corridors. Although we have a 2D image, the differences between the broken edges of the pattern allow us to find out the depth. A variety of laser patterns have been analyzed and tested in a simulated environment of an automated store made by walls, doors, and corridors. The results have led us to improve a pattern that permits a high level of reliability in the autonomous indoor navigation. The robustness of the model has allowed us to move forward on the unexpected obstacles detection which generate deformations on the wished patterns. The system also permits the detection of slopes and columns located on its way.