Multi Sensor

Multi-sensor systems integrate data from diverse sources (e.g., cameras, LiDAR, radar, IMUs) to achieve more robust and comprehensive environmental perception than single sensors alone. Current research emphasizes developing efficient fusion algorithms, often employing deep learning architectures like convolutional neural networks (CNNs) and factor graphs, to combine sensor data for tasks such as autonomous navigation, object recognition, and health monitoring. These advancements are driving progress in robotics, autonomous vehicles, and other fields by enabling more reliable and accurate data interpretation in complex and dynamic environments.