With the emerging interest in the autonomous driving level at 4 and 5 comes a necessity to
provide accurate and versatile frameworks to evaluate the algorithms used in autonomous …

Real-time six degrees-of-freedom pose estimation with ground vehicles represents a
relevant and well-studied topic in robotics due to its many applications such as autonomous …

This paper presents an approach to implem enting centralized multirobot simultaneous
localization and mapping (MR-SLAM) in an unknown environment based on LiDAR sensors …

Accurate 3D point cloud map generation is a core task for various robot missions or even for
data-driven urban analysis. To do so, light detection and ranging (LiDAR) sensor-based …

Modern LiDAR SLAM systems have shown remarkable performance and ability to operate in
various environments ranging from indoor offices to large natural environments such as …

The current LiDAR SLAM (Simultaneous Localization and Mapping) system suffers greatly
from low accuracy and limited robustness when faced with complicated circumstances. From …

Point cloud preprocessing lays the foundation for the realization of autonomous vehicles
(AVs) as it is the backbone of 3D LiDAR simultaneous localization and mapping (SLAM) …

Simultaneous localization and mapping (SLAM) is essential for intelligent robots operating
in unknown environments. However, existing algorithms are typically developed for specific …

Numerous researchers have conducted studies to achieve fast and robust ground-optimized
LiDAR odometry methods for terrestrial mobile platforms. In particular, ground-optimized …

Mobile mapping technologies, based on techniques such as simultaneous localization and
mapping (SLAM) and surface-from-motion (SfM), are being vigorously developed both in the …