Dynamic model-based augmented extended Kalman filter for real time simulation of mobile robots

This paper presents a new design of augmented extended Kalman filter (AEKF) based on the dynamic model for real-time simulation of mobile robots. The dynamic model is composed of two consecutive parts; kinematic model and equations of linear and angular torques. A Simulink^reg model is developed for simultaneous localization and odometry calibration of mobile robots in real time manner. Assuming an absolute measurement available, the AEKF provides the local reconstruction of mobile robots position and orientation with an on-line odometry calibration. Furthermore, it gives estimations for the linear and angular velocities of the robot that can be used for control strategy. The simulation results verify the effectiveness of the proposed method and suggest it as a promising way for real time control of mobile robots.