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 …

Place recognition is an important component for autonomous vehicles to achieve loop
closing or global localization. In this article, we tackle the problem of place recognition …

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 …

Many existing datasets for lidar place recognition are solely representative of structured
urban environments, and have recently been saturated in performance by deep learning …

Place Recognition enables the estimation of a globally consistent map and trajectory by
providing non-local constraints in Simultaneous Localisation and Mapping (SLAM). This …

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

LiDAR-based place recognition (LPR) is one of the most crucial components of autonomous
vehicles to identify previously visited places in GPS-denied environments. Most existing LPR …

Recognizing places using Lidar in large-scale environments is challenging due to the
sparse nature of point cloud data. In this letter we present BVMatch, a Lidar-based frame-to …

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 …

We propose a methodology for robust, real-time place recognition using an imaging lidar,
which yields image-quality high-resolution 3D point clouds. Utilizing the intensity readings of …