Vehicle Positioning

Precise vehicle positioning is crucial for autonomous navigation and various mapping applications, particularly in challenging environments where Global Navigation Satellite Systems (GNSS) are unreliable. Current research focuses on improving accuracy through sensor fusion, leveraging data from inertial measurement units (IMUs), LiDAR, and detailed 3D maps to enhance GNSS or create GNSS-independent positioning systems. This involves employing machine learning techniques like convolutional neural networks and random forests to process sensor data and refine positioning estimates, as well as developing advanced algorithms for ambiguity resolution in GNSS carrier phase measurements. These advancements are vital for enabling safer and more efficient autonomous vehicles and improving the accuracy of various mapping tasks, including underwater bathymetry.