Motivated by the goal of achieving robust, drift-free pose estimation in long-term
autonomous navigation, in this work we propose a methodology to fuse global positional …

Visual odometry and SLAM methods have a large variety of applications in domains such as
augmented reality or robotics. Complementing vision sensors with inertial measurements …

Visual-Inertial Odometry (VIO) algorithms typically rely on a point cloud representation of the
scene that does not model the topology of the environment. A 3D mesh instead offers a …

In this paper, we present a novel approach to tightly couple visual and inertial
measurements in a fixed-lag visual-inertial odometry (VIO) framework using information …

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 …

Visual Inertial Odometry (VIO) is one of the most established state estimation methods for
mobile platforms. However, when visual tracking fails, VIO algorithms quickly diverge due to …

In recent years there have been excellent results in visual-inertial odometry techniques,
which aim to compute the incremental motion of the sensor with high accuracy and …

In this paper, we propose a novel robocentric formulation of the visual–inertial navigation
system (VINS) within a sliding-window filtering framework and design an efficient …

Cameras and inertial measurement units are complementary sensors for ego-motion
estimation and environment mapping. Their combination makes visual-inertial odometry …

Flying robots require a combination of accuracy and low latency in their state estimation in
order to achieve stable and robust flight. However, due to the power and payload constraints …