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Aiming at the problem of simultaneous localization and mapping(SLAM) for mobile robots,an improved EKF-SLAM algorithm was proposed while considering the existing defects of extended Kalman (EKF) algorithm-not suitable for a large number of characters,occasions such as a wide range of environments ,an intensive environment and so on.It put the decomposition thought of Rao-Blackwellise on the extended Kalman (EKF) algorithm-Decomposition Estimate framework ,which broke down the SLAM problem into the two issues of the path estimation and map estimation so that predicting,observating,updating and increasing vectors .The simulation results show that improved EKF-SLAM algorithm is more superior than EKF-SLAM algorithm in a number of features,occasions. The improved algorithm greatly reduces the computational complexity and improves the accuracy so it provides an effective method for the problem of simultaneous localization and mapping (SLAM) for mobile robots in the more complex environment.