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Summary form only given. In this paper, we propose a method for increasing the accuracy of the estimated position of a mobile robot by its internal sensors, rotary encoders and an optical fiber gyroscope. We use the extended Kalman filter theory to combine the encoder data and optical fiber gyroscope data. This enables us to compensate the effect of the variance of wheels. Validity of the proposed algorithm is tested by computer simulations and experiments. The results obtained show that the errors between the estimated position and the real position were reduced by using our method. For experiment purpose, we have developed a mobile robot called MUSEAR (multiple sensor autonomous rover).