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

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

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 …

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 …

We introduce a novel method for oriented place recognition with 3D LiDAR scans. A
Convolutional Neural Network is trained to extract compact descriptors from single 3D …

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 …

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 …

Compared to diverse feature detectors and descriptors used for visual scenes, describing a
place using structural information is relatively less reported. Recent advances in …

Place recognition is a critical component towards addressing the key problem of
Simultaneous Localization and Mapping (SLAM). Most existing methods use visual images; …

3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-
challenged environments and serves as an essential component (ie loop-closure detection) …