Example Concept: Multi-modal sensor integration requires combining data from various sources such as LiDAR, cameras, IMUs, and GPS to create a coherent understanding of the environment. The primary challenges include ensuring temporal and spatial synchronization of sensor data, managing the different data rates and formats, and effectively fusing this information to handle uncertainties and noise. Robust algorithms like Kalman filters, particle filters, or deep learning-based fusion techniques are often employed to achieve reliable sensor fusion.