LiDAR-based place recognition (LPR) plays a pivotal role in autonomous driving, which
assists Simultaneous Localization and Mapping (SLAM) systems in reducing accumulated …

Place recognition is an important capability for autonomously navigating vehicles operating
in complex environments and under changing conditions. It is a key component for tasks …

Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for
autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved …

LiDAR-based place recognition (LPR) is one of the basic capabilities of robots, which can
retrieve scenes from maps and identify previously visited locations based on 3D point …

Abstract Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. Over the last two decades …

Place recognition is an important branch of Simultaneous Localization and Mapping
(SLAM), which finds revisited places, thereby reducing error accumulations. Most …

Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. In the last two decades, LiDAR …

To execute collaborative tasks in unknown environments, a robotic swarm must establish a
global reference frame and locate itself in a shared understanding of the environment …

Place recognition retrieves scenes from a prior map and identifies previously visited
locations. It is essential to autonomous-driving and robotics in terms of long-term navigation …

Global localization plays a critical role in many robot applications. LiDAR-based global
localization draws the community's focus with its robustness against illumination and …