The kidnapped robot is a well-known problem in mobile robotics; it is a special case of the global localization problem, which arises when the robot is physically moved to another location without its knowledge, or gets lost in the environment. Kidnapped Robot Problem is usually studied and tested to evaluate the performance of localization algorithms since none of them can guarantee not to fail. In this thesis, we propose a solution in order to solve the kidnapped robot problem in dynamic and similar environment based on Visual Place Recognition (VPR), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to initialise the position of the robot and a particle filter to correct the pose.