IRobot self-localization using EKF

Abstract

Self-Localization plays an important role in the mobile robot autonomous navigation. The Wheel Mobile robot usually contains a large number of different sensors, such as odometry, gyro, laser, camera and so on. All these sensors provide the information of robot localization and all these information should be considered for the optimal location. However, for the cost of the iRobot, we could not be equipped with a lot of sensors. We have only encoder sensor and gyro sensor. So this paper researches mobile robot localization only using odometer and gyro sensor based on Extended Kalman Filter (EKF). The method is that the iRobot fuses the messages from encoder sensor and gyro sensor by EKF theory, which can collect the errors that obtained the robot's orientation and position. The experiment results appear that the proposed self-localization method is effective and feasible.