For the error value and divergence problem in the application of traditional Kalman filtering algorithm and extended Kalman filtering algorithm in mobile robot positioning system, the modification factor was introduced into the localization algorithm to optimize the state estimation equation. The positioning algorithm theories of traditional Kalman filtering and extended Kalman filtering were analyzed, and the influence of driving force and friction force on mobile robot was researched. Finally the modification factor was introduced to improve the Kalman filter algorithm, and the traditional Kalman filter algorithm, extended Kalman filtering algorithm and improved algorithm were compared by simulation results. The simulation results show that modification factor improves the classical Kalman filtering algorithm and the extended Kalman filter algorithm and it also improves the positioning accuracy.