Example Concept: Sensor fusion in robotics often utilizes algorithms like the Extended Kalman Filter (EKF) or Particle Filter to integrate data from various sensors. By fusing data, these algorithms can smooth out noise, correct for drift, and provide a more robust estimate of the robot's state. For instance, while an IMU may provide high-frequency motion data, it can drift over time; combining it with GPS or LIDAR data can correct this drift, resulting in more accurate localization.