Error pose correction of mobile robot for SLAM problem using laser range finder based on particle filter

This paper presents the implementation of the particle filter (PF) to solve the simultaneous localization and mapping (SLAM) problem in mobile robot, particle filter is used to localize the mobile robot with a laser range finder (LRF) sensor. On this experiment we used the real data that taken from our robot. We used the weighted mean in a small window around the best particle called robust mean as the method of selection and calculation weight in every particle. The experiment result shows that the proposed particle filter can improve the performance and give more robustness of mobile robot localization inside our building.