Example Concept: Sensor fusion in robotics typically involves using algorithms like the Kalman Filter or Extended Kalman Filter to integrate data from various sensors. For instance, an IMU provides high-frequency orientation data, while GPS offers absolute position information. By fusing these inputs, the robot can achieve a more accurate and stable localization, even in environments where one sensor may be unreliable or unavailable.