Auto Perception with Multi-modal Sensor Fusion

Auto driving perception heavily relies on the accuracy and integration of multiple sensor inputs, including cameras, radars, and lidars. This survey proposes an approach for auto perception using multi-modal sensor fusion to achieve higher performance and robustness. Through the fusion of data from different sensors, the system can create a more comprehensive representation of the environment, enable real-time processing, and improve decision-making. Overall, this survey highlights the importance of multi-modal sensor fusion in autonomous driving and future research directions.