Localization Framework

Localization frameworks aim to determine the precise position and orientation of a system (e.g., robot, vehicle) within a known or unknown environment. Current research emphasizes robust and efficient methods using diverse sensor data (LiDAR, radar, cameras, GPS) integrated through techniques like graph-based SLAM, particle filters, and deep neural networks, often incorporating prior map information or learned representations. These advancements are crucial for enabling autonomous navigation in robotics, autonomous driving, and augmented reality applications, improving accuracy and reliability even in challenging or dynamic environments.