Vehicle Localization
Vehicle localization, the process of determining a vehicle's precise position and orientation, is crucial for autonomous driving and robotics. Current research emphasizes robust and efficient localization methods, even under challenging conditions like GPS signal loss or adverse weather, often employing sensor fusion techniques (e.g., GPS/IMU, camera/LiDAR) and advanced algorithms such as particle filters, Kalman filters, and transformer networks. These advancements leverage various data sources, including maps (both standard definition and high-resolution semantic maps), point clouds, and image features, to improve accuracy and reliability, ultimately contributing to safer and more effective autonomous navigation systems.
Papers
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