We describe a new technique for landmark-based self-localization which is suitable for robots with poor odometry. This technique uses fuzzy logic to account for errors and imprecision in visual recognition, and for extreme uncertainty in the estimate of the robot's motion. It only requires an approximate model of the sensor system and a qualitative estimate of the robot's displacement, and it has a moderate computational cost. We show examples of use of our technique on a Sony AIBO legged robot in the RoboCup domain.