Example Concept: Sensor fusion involves integrating data from various sensors such as GPS, IMUs, LIDAR, and cameras to improve localization. For instance, while GPS provides global position data, it may be inaccurate in urban environments. IMUs offer high-frequency motion data but can drift over time. LIDAR provides precise distance measurements but lacks global context. By fusing these data sources, the robot can achieve a more accurate and robust localization solution, compensating for the limitations of individual sensors.