Example Concept: Sensor fusion integrates data from various sensors such as LiDAR, cameras, and ultrasonic sensors to improve obstacle detection. By fusing data, the system can compensate for the weaknesses of each sensor type — for instance, LiDAR provides accurate distance measurements, while cameras offer rich visual context. The fusion process typically involves algorithms like Kalman filters or particle filters to combine sensor inputs, resulting in a more accurate and reliable obstacle map.