SLAM based on intelligent unscented Kalman filter

The performance of SLAM based on unscented Kalman filter (UKF-SLAM) and thus the quality of the estimation depends on the correct a priori knowledge of process and measurement noise. Imprecise knowledge of these statistics can cause significant degradation in performance. In this paper, the adaptive Neuro-Fuzzy has been implemented to adapt the matrix covariance process of UKF-SLAM in order to improve its performance.