Optimization of improved extended Kalman filter for mobile robot Navigation

The Kalman filter is widely used in different applications, such as signal processing, modem control, and communication. It is instrumental in estimating system states with unknown statistics. The application can be significant in improving the accuracy and precision of state estimation for both linear and non-linear systems. The Extended Kalman Filter (EKF) is one of the important methods for the non-linear application of the Kalman filter, among other variations. The resulting expressions exhibit unity in that they apply to different situations involving localization procedures. This work presents the optimization of an improved EKF for mobile robot navigation by finding the best ways to reduce the time taken to complete the job.