In this paper, we present a method for the absolute localization of a mobile robot, moving through a flat environment cluttered with cylindrical obstacles of any shape. The robot has in memory a list of coordinates of some points used as a map of the environment, and is provided with a laser rangefinder giving range distances to the obstacles in several known directions. The obstacles themselves are used as references of position, that eliminates the need for landmarks. First we explain the method, looking like the Hough methods, deducing the absolute position and the attitude of the robot, by matching the range measurements to the environment map. The quality of the matching between the two lists of points is eva-luated through a test of accumulation. The rapidity and the precision of the method are studied in terms of the number of range measurements. Finally we show that the use of the relative localization, estimated by odometry, allows considerable speed up of the algorithm and reduces simultaneously the number of range measurements. Then the localization can be processed without stopping the robot. The absolute localization periodically computed, allows the resetting of the position estimated by odometry, and both systems form a means of localization allowing the robot to be guided along any trajectory.