The continuous advancement of autonomous systems has significantly accelerated the evolution of industrial automation, aligning with the objectives of Industry 4.0. This thesis investigates the hardware implementation of navigation systems for Autonomous Ground Vehicles (AGVs), with a particular focus on Hardware-in-the-Loop (HIL) testing. The research employs state-of-the-art Simultaneous Localization and Mapping (SLAM) techniques and navigation algorithms within the Robot Operating System 2 (ROS2) framework, aiming to enhance AGVs’ localization, mapping, and obstacle avoidance capabilities in both indoor and outdoor environments. Multiple SLAM methods were explored, including SLAM Toolbox, Cartographer, and LIO-SAM, to identify the most effective algorithm for accurate mapping and localization.