With the rapid advancements of sensor technology and deep learning, autonomous driving
systems are providing safe and efficient access to intelligent vehicles as well as intelligent …

Point set registration is the technology used to estimate the spatial transformation between
two LiDAR scans, which is challenging in the presence of outlier correspondences and …

Estimating the rigid transformation between two LiDAR scans through putative 3D
correspondences is a typical point cloud registration paradigm. Current 3D feature matching …

Point set registration is an essential technique in the field of machine vision. In this article,
we propose a robust global optimal solution to for the point set registration of feature points …

Sensor fusion is essential for autonomous driving and autonomous robots, and radar-
camera fusion systems have gained popularity due to their complementary sensing …

Point cloud registration is challenging in the presence of heavy outlier correspondences.
This paper focuses on addressing the robust correspondence-based registration problem …

Most vision-based sensing and localization infrastructure today employ conventional area
scanning cameras due to the high information density and cost efficiency offered by them …

Multi-vehicle collaborative mapping proves more efficient in constructing maps in unfamiliar
underwater environments in comparison to single-vehicle methods. One of the pivotal …

Robust and accurate perception is important for modern intelligent transportation systems
(ITS), which use sensors of various modalities for data fusion to create a digital twin of an …

While automotive radar sensors are widely adopted and have been used for automatic
cruise control and collision avoidance tasks, their application outside of vehicles is still …