Example Concept: Sensor fusion in robotics often involves integrating data from sources like GPS, IMUs, and cameras using algorithms such as the Extended Kalman Filter (EKF) or Particle Filter. These algorithms process the sensor inputs to estimate the robot's state, reducing uncertainty and improving robustness against sensor noise and errors. By fusing data, the system can maintain accurate localization even in environments where individual sensors might fail, such as GPS-denied areas or visually challenging conditions.