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

Abstract Visual Place Recognition is a challenging task for robotics and autonomous
systems, which must deal with the twin problems of appearance and viewpoint change in an …

We propose a framework for tightly-coupled lidar inertial odometry via smoothing and
mapping, LIO-SAM, that achieves highly accurate, real-time mobile robot trajectory …

Visual place recognition has attracted widespread research interest in multiple fields such
as computer vision and robotics. Recently, researchers have employed advanced deep …

Simultaneous localization and mapping (SLAM) is a fundamental capability required by
most autonomous systems. In this paper, we address the problem of loop closing for SLAM …

Loop closure detection is an essential and challenging problem in simultaneous localization
and mapping (SLAM). It is often tackled with light detection and ranging (LiDAR) sensor due …

Localization and mapping are key capabilities of autonomous systems. In this paper, we
propose a modified Siamese network to estimate the similarity between pairs of LiDAR …

Abstract Visual Place Recognition (VPR) is often characterized as being able to recognize
the same place despite significant changes in appearance and viewpoint. VPR is a key …

无人平台在大范围环境中实现自主定位与导航的能力需求日益严苛, 其中基于激光雷达的同步
定位和绘图技术(SLAM) 是主流的研究方案. 在这项工作中, 本文系统概述了3D 激光雷达SLAM …

Although Global Navigation Satellite Systems (GNSSs) generally provide adequate
accuracy for outdoor localization, this is not the case for indoor environments, due to signal …