Example Concept: Sensor fusion involves integrating data from various sensors to improve the accuracy and robustness of a robot's perception system. By fusing inputs from cameras, LIDAR, and IMUs, a robot can better estimate its position, detect obstacles, and navigate complex environments. This process typically uses algorithms like Kalman filters or particle filters to merge sensor data, reducing noise and compensating for individual sensor weaknesses.