Example Concept: Sensor fusion in autonomous navigation combines inputs from various sensors such as LIDAR, cameras, IMUs, and GPS to enhance perception accuracy. The primary challenge is to filter and integrate these diverse data streams in real-time, accounting for discrepancies in sensor resolution, update rates, and noise characteristics. Techniques like Kalman filters, particle filters, and deep learning models are often employed to achieve a cohesive and reliable environmental model.