In the face of large-scale environmental map** requirements, through the use of
lightweight and inexpensive robot groups to perceive the environment, the multi-robot …

In this paper, we focus on the problem of motion tracking in unknown environments using
visual and inertial sensors. We term this estimation task visual–inertial odometry (VIO), in …

This paper presents SVIn2, a novel tightly-coupled keyframe-based Simultaneous
Localization and Map** (SLAM) system, which fuses Scanning Profiling Sonar, Visual …

The high-precision localization module is an essential component of unmanned underwater
vehicles (UUVs), providing critical parameter information for motion control, decision …

This paper presents a novel tightly-coupled keyframe-based Simultaneous Localization and
Map** (SLAM) system with loop-closing and relocalization capabilities targeted for the …

We present a new dataset, dedicated to the development of simultaneous localization and
map** methods for underwater vehicles navigating close to the seabed. The data …

A plethora of state estimation techniques have appeared in the last decade using visual
data, and more recently with added inertial data. Datasets typically used for evaluation …

When fusing visual and inertial measurements for motion estimation, each measurement's
sampling time must be precisely known. This requires knowledge of the time offset that …

In this paper, we propose an approach for robust visual Simultaneous Localisation and
Map** (SLAM) in underwater environments leveraging acoustic, inertial and …

In the underwater domain, guaranteeing accurate navigation for an autonomous underwater
vehicle (AUV) is a complex but fundamental task to be achieved. As a matter of fact, only by …