In the rapidly evolving landscape of automation, robots and autonomous vehicles have become essential tools, driving innovation, improving efficiency and reliability, while integrating and cooperating with humans. This thesis presents the development of an Autonomous Mobile Robot (AMR) system based on the Yahboom ROSMASTER X3, from the assembly phase to code implementation. The system is powered by a NVIDIA Jetson Nano and actuated by a STM32-based board. The robot is equipped with a depth camera and a LiDAR sensor. The robot primary function is to track a moving target in real time while autonomously avoiding obstacles. The person detection is based on a previous thesis project on neural networks and real-time object tracking.