Example Concept: Sensor fusion involves integrating data from various sensors like LIDAR, cameras, and IMUs to improve the accuracy and robustness of a robot's perception system. By leveraging complementary strengths of different sensors, such as the high resolution of cameras and the precise distance measurement of LIDAR, sensor fusion algorithms can provide a more accurate and reliable estimation of the robot's surroundings, enhancing tasks like localization, mapping, and obstacle detection.