Example Concept: Sensor fusion for robot localization typically employs algorithms such as the Extended Kalman Filter (EKF) or Particle Filters to merge data from diverse sensors. These algorithms help mitigate individual sensor inaccuracies by leveraging the strengths of each sensor type, such as the high precision of LIDAR and the broad coverage of GPS. The fusion process must account for temporal synchronization, coordinate transformation, and noise filtering to enhance the robot's position and orientation estimation.