Example Concept: Sensor fusion involves merging data from various sensors like LiDAR, cameras, IMUs, and GPS to improve the robot's situational awareness. By integrating these diverse data sources, the robot can compensate for the limitations of individual sensors, such as the limited field of view of a camera or the susceptibility of GPS to signal loss. This comprehensive perception is essential for tasks like obstacle detection, localization, and path planning, enabling the robot to operate autonomously with higher precision and reliability.