An SLAM algorithm based on improved UKF

Because of using system nonlinear model directly UKF overcomes the shortcomings of the methods such as EKF that they easily introduces truncation errors in the process of lining model .So it is widely used in SLAM problem. Because the square root of filter has the advantages that it can ensure the covariance matrix nonnegative, a square root version of the UKF was included in the SLAM problem that improve the performance of UKF-SLAM algorithm. Simulation result shows that this algorithm is effective.