The rapid advancement of autonomous systems and automation technologies continues to revolutionize industrial processes, aligning with the goals of Industry 4.0. This thesis presents an enhanced Autonomous Mobile Robot (AMR) system intended for advanced indoor navigation and exploration, building on the groundwork established by the FIXIT project at CIM4.0. The primary objective of this research is to develop and implement a robust SLAM (Simultaneous Localization and Mapping) algorithm utilizing the latest capabilities of ROS2 (Robot Operating System 2). A key focus of this study is a comprehensive comparison of different SLAM approaches using the Nav2 library within the ROS2 framework. This analysis covers various algo??rithms available in Nav2, including grid-based and topological mapping methods, as well as different localization techniques such as AMCL (Adaptive Monte Carlo Localization) and EKF (Extended Kalman Filter).