Accurate and robust localization is a fundamental requirement for safe autonomous driving.
Currently, most vehicles rely on single-vehicle localization (SVL) using the global navigation …

Although cooperative localization (CL) is fundamental to multirobot systems, current
algorithms suffer from the tracking of interdependencies, information fusion from multiple …

Point Cloud Registration (PCR) has been viewed as an essential part of photogrammetry,
remote sensing, and autonomous robot mapping. Existing methods are either sensitive to …

Cooperative perception is a promising technique for intelligent and connected vehicles
through vehicle-to-everything (V2X) cooperation, provided that accurate pose information …

In the context of autonomous driving systems, SLAM and dynamic object tracking represent
pivotal challenges. Autonomous driving scenarios frequently demand the simultaneous …

Vehicle localization plays a crucial role in ensuring the safe operation of autonomous
vehicles and the development of intelligent transportation systems (ITS). However, there is …

This paper considers the problem of cooperative localization of passive objects in a
vehicular environment through the fusion of lidar point clouds collected at different moving …

Decentralized cooperative localization (DCL) exhibits significant advantages in fault
tolerance, practicality, and scalability, which serves as a crucial prerequisite for multirobot …

To support various upper applications of intelligent vehicles ranging from driving assistance
to automated planning and control, accurate localization, and tracking are the fundamental …

Point cloud registration is a critical research area in computer vision with extensive
applications. Recent studies have unveiled the significant potential of graph neural networks …