Integration of multiple sensor modalities and deep learning into Simultaneous Localization
And Mapping (SLAM) systems are areas of significant interest in current research. Multi …

We introduce a new system for Multi-Session SLAM which tracks camera motion across
multiple disjoint videos under a single global reference. Our approach couples the …

In this paper, we present an efficient visual SLAM system designed to tackle both short-term
and long-term illumination challenges. Our system adopts a hybrid approach that combines …

Accurate and robust vehicle localization in highly urbanized areas is challenging. Sensors
are often corrupted in those complicated and large-scale environments. This article …

In order to realize the independent and safe operation of trenching robot in Camellia oleifera
forest, operation path planning is the key link. Aiming at the problem of trenching operation …

For long-duration operations in GPS-denied environments, accurate and repeatable
waypoint navigation is an essential capability. While simultaneous localization and mapping …

Abstract Visual Semantic Navigation (VSN) is the ability of a robot to learn visual semantic
information for navigating in unseen environments. These VSN models are typically tested in …

We propose in this letter a tightly-coupled fusion of visual, inertial and magnetic data for long-
term localization in indoor environment. Unlike state-of-the-art Visual-Inertial SLAM …

In health care, a telepresence robot could be used to have a clinician or a caregiver assist
seniors in their homes, without having to travel to these locations. However, the usability of …

Precisely estimating a vehicle's pose in a prior map is a fundamental capability for
autonomous driving. This task, however, remains challenging in low-texture and semi-static …