Example Concept: Sensor fusion in robotics involves combining data from different sensors, such as LiDAR, cameras, and IMUs, to improve the accuracy and reliability of perception systems. This process requires algorithms that can manage discrepancies in data timing, resolution, and noise characteristics, often employing techniques like Kalman filters, particle filters, or deep learning models to achieve robust environmental understanding.