Combination of MCL and ICP methods for accurate indoor localization

Nowadays, mobile robots that are widely used in the industry are moving on pre-planned paths. These paths are prepared using wires, magnetic tapes or any other methods that allow the robot to follow the path. However, using these paths restricts the movement of the robot. This is because when it is necessary to change the target locations of the robot in the factory, the paths have to be prepared from the very beginning in accordance with the new task of the robot. Doing this will cause extra cost and time loss. For these reasons, mobile robots used in the industry need to reach the target without any help, instead of moving on predetermined paths as they go to the target position. In order to do this, they need to know their current pose. In this thesis, the localization study for indoor mobile robots that are used in the industry was performed in the simulation environment by using a two-step indoor localization method. In the first step of the localization method, the pose of the robot was roughly estimated and then its pose was roughly tracked in a known environment by using the Monte Carlo Localization algorithm. In the second step, when the robot was close to a predetermined target point, the instantaneous pose of the robot was accurately estimated by using a variant of ICP algorithm.