In a context where robotics and autonomous vehicles are becoming increasingly central in industry and research, this thesis presents the development of an autonomous driving system for Yahboom ROSMASTER X3 educational robot. The main objective is the implementation of a rover capable of autonomously following a line and recognising road signs by integrating sensor fusion techniques between LiDAR and a depth camera. This combination allows the robot to obtain a more accurate perception of its surroundings, enhancing navigation adaptability to complex scenarios. The system is based on ROS2 and exploits a hardware platform consisting of an NVIDIA Jetson Nano for image processing and autonomous navigation and Mecanum wheels that provide omnidirectional mobility, improving the robot manoeuvring capabilities.