Mobile robot localization based on Extended Kalman Filter

The mobile robot localization methodologies in common use at present have been introduced. A localization algorithm based on Extended Kalman Filter (EKF) has been proposed on the basis of environment feature extraction and map building, which can reduce the error in the calculation of the robot's position and orientation. The method is that the mobile robot analyses and fuses the messages in surroundings from multiple sensors by EKF theory, which enables the robot to identify the surrounding objects clearly and guide itself successfully. The simulation and experimental results show that the proposed localization method is effective.