Example Concept: Sensor fusion in robotics often employs the Kalman filter, which is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone. This method is particularly useful in robotics for integrating data from various sensors to improve the robot's perception and decision-making capabilities.