In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown
significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous …

Recently, with the in-depth development of Industry 4.0 worldwide, mobile robots have
become a research hotspot. Indoor localization has become a key component in many fields …

Although deep learning-based stereo matching approaches have achieved excellent
performance in recent years, it is still a non-trivial task to estimate the uncertainty of the …

Static environment is a prerequisite for most of visual simultaneous localization and
mapping systems. Such a strong assumption limits the practical application of most existing …

Abstract Simultaneous Localization and Mapping (SLAM) is a key problem in the field of
Artificial Intelligence and mobile robotics that addresses the problem of localization and …

Abstract Simultaneous Localization and Mapping is the process of simultaneously creating a
map of the environment while navigating in it. Most of the SLAM approaches use natural …

The COVID-19 pandemic has affected many countries, posing a threat to human health and
safety, and putting tremendous pressure on the medical system. This paper proposes a …

TagSLAM provides a convenient, flexible, and robust way of performing Simultaneous
Localization and Mapping (SLAM) with AprilTag fiducial markers. By leveraging a few simple …

Smartphone camera or inertial measurement unit (IMU) sensor-based systems can be
independently used to provide accurate indoor positioning results. However, the accuracy of …

Automated visual data collection using autonomous unmanned aerial vehicles (UAVs) can
improve the accessibility and accuracy of the frequent data required for indoor construction …