In this paper an approach to real-time position correction and environmental modeling based on odometry, ultrasonic sensing, structured light sensing and active stereo vision (bin- and trinocular) is presented. Odometry provides the robot with a position estimation and with the help of a model of the environment sensor perceptions can be matched to predictions. Ultrasonic sensing is capable of collision avoidance and obstacle detection and so enables navigation in simply structured environments. Model-based image processing allows detection and classification of natural landmarks in the stereo images uniquely. With only one observation the robot's position and orientation relative to the observed landmark is found precisely. This sensing strategy is used when high precision is necessary for the performance of the navigation task. Finally techniques are described that allow an automatic mapping of an unknown or only partially known environment.