Example Concept: Sensor fusion combines inputs from various sensors such as LIDAR, cameras, IMUs, and GPS to improve a robot's situational awareness. By merging these data streams, the robot can filter out noise, reduce uncertainty, and enhance the accuracy of its state estimation. This fusion process often utilizes algorithms like the Kalman Filter or Particle Filter, which weigh the reliability of each sensor input to produce a cohesive and precise representation of the environment.