A Study on the Kalman Filter Based PID Controller for Mecanum-wheeled Mobile Robot

Abstract Recently, the mecanum-wheeled mobile robot (MWMR) has been widely adopted in many industries because of its enhanced mobility and the ability of the mecanum wheel (sometimes called the Swedish wheel). However, this implementation will increase the complexity of the robot, resulting in the phenomena of slip or vibration. On the other hand, the Kalman filter has remained a cornerstone in system state estimation and is an effective tool in the noise-reducing process. Therefore, this study aims to design a PID controller, which is used popularly in the industrial landscape, with the integration of the Kalman filter to reduce the noise within the operation of the robot system. This approach has rarely been explored in academic literature, to address this gap, this research will build a mechanical model and implement it into the Matlab/Simulink environment for simulation. At its core, the study aims to harness the predictive capabilities of the Kalman filter, integrating it with the PID controller to minimize MWMR errors during operation. Through this integrated methodology, the paper has proved the value of the Kalman filter when integrating with PID by comparing the results with the non-Kalman filter cases.