Multi-Sensor Fusion is the process of combining data from multiple sensors to generate a more accurate and comprehensive understanding of an environment than could be achieved by any of the sensors individually. By leveraging the strengths of each sensor, multi-sensor fusion can provide a more complete picture of a situation than could be obtained from any single sensor. This is accomplished through the integration of the different sensor data sets by applying algorithms such as Kalman filtering and Bayesian networks to generate a unified output.