The position and orientation estimation problem for mobile robots is approached by fusing measurements from inertial sensors, wheel encoders, and a camera. The sensor fusion approach is based on the standard extended Kalman filter, which is modified to handle measurements from the camera with unknown prior delay. A real-time implementation is done on a four-wheeled omni-directionalmobile robot, using a dynamicmodelwith 11 states. The algorithmis analyzed and validated with simulations and experiments.