Enhancement of mobile robot localization using extended Kalman filter

Journal Article

, Mohammed Faisal, Mansour Alsulaiman, Ramdane Hedjar, Hassan Mathkour, Mansour Zuair, Hamdi Altaheri, Mohammed Zakariah, Mohammed A. Bencherif, and Mohamed . 2016

مستخلص المنشور

In this article, we introduce a localization system to reduce the accumulation of errors existing in the dead-reckoning
method of mobile robot localization. Dead-reckoning depends on the information that comes from the encoders. Many
factors, such as wheel slippage, surface roughness, and mechanical tolerances, affect the accuracy of dead-reckoning.
Therefore, an accumulation of errors exists in the dead-reckoning method. In this article, we propose a new localization
system to enhance the localization operation of the mobile robots. The proposed localization system uses the extended
Kalman filter combined with infrared sensors in order to solve the problems of dead-reckoning. The proposed system
executes the extended Kalman filter cycle, using the walls in the working environment as references (landmarks), to correct errors in the robot’s position (positional uncertainty). The accuracy and robustness of the proposed method are
evaluated in the experiment results’ section.