Example Concept: Sensor fusion involves integrating data from various sensors to enhance the accuracy and robustness of obstacle detection. For instance, LIDAR provides precise distance measurements, while cameras offer rich visual information. By fusing these data streams, a robot can achieve better spatial awareness and obstacle recognition, reducing false positives and improving navigation safety. Techniques like Kalman filtering or Bayesian networks are often used to combine sensor inputs effectively.