Robots that can move autonomously and can make intelligent decisions by perceiving their
environments and surrounding objects are known as autonomous mobile robots. Such …

Loop closure detection is of vital importance in the process of simultaneous localization and
mapping (SLAM), as it helps to reduce the cumulative error of the robot's estimated pose and …

Place recognition is a key module in robotic navigation. The existing line of studies mostly
focuses on visual place recognition to recognize previously visited places solely based on …

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 …

Multi-beam LiDAR sensors are increasingly used in robotics, particularly with autonomous
cars for localization and perception tasks, both relying on the ability to build a precise map of …

The rapid development of autonomous driving and mobile mapping calls for off-the-shelf
LiDAR SLAM solutions that are adaptive to LiDARs of different specifications on various …

Robust and accurate, map-based localization is crucial for autonomous mobile systems. In
this paper, we exploit range images generated from 3D LiDAR scans to address the problem …

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 …

A holistic semantic scene understanding exploiting all available sensor modalities is a core
capability to master self-driving in complex everyday traffic. To this end, we present the …

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 …