Mobile robot localization with extended kalman filter

ABSTRACTMOBILE ROBOT LOCALIZATION WITH EXTENDED KALMAN FILTERK. Hasan HatipoğluBaşkent University Institute of ScienceThe Department of Electrical and Electronics EngineeringOne of the most important and necessary features of the autonomous mobilerobots to perform their functions in the environment is their ability to know theirlocations. Robots can analyze the features of their environment correctly as longas they know their own positions. In general, two types of measurement methodsare used for robot localization. They are absolute and relative measurementmethods. Usually, these two measurement methods are used together.In this thesis, both absolute and relative measurement methods were utilized tolocalize the robot. Sonar sensors and optical shaft encoders were used forabsolute and relative measurements respectively. These sensors and kinematicalrobot systems were modeled, and extended Kalman filter was used in order toreduce the odometric errors in orientation and position of the mobile robot.In experimental work, Pioneer 3-DX, an autonomous mobile robot with 8 sonarsand two optical encoders located on the wheels was used. Localization of themobile robot was performed in a closed indoor environment. The efficiency of themobile robot localization performed by using odometry and sensor fusion methodswere compared with the simulation and physical environment experiments. Therequired software was developed by using Matlab. It is observed that last positionerror of the mobile robot is decreased with the use of EKF.Keywords: Navigation, Localization, Extended Kalman Filter, OdometryAdvisor: Asst. Hamit Erdem, Başkent University, The Department of Electricaland Electronics Engineering.ii