Example Concept: Sensor fusion in robotics typically involves integrating data from various sensors using algorithms like the Kalman Filter or Particle Filter. These algorithms process noisy sensor inputs to produce a single, refined estimate of the robot's state. By fusing data from sensors with complementary characteristics—such as the high accuracy of LIDAR with the broad coverage of GPS—robots can maintain accurate localization even when individual sensors are unreliable or obstructed.