Simultaneous Localization and Map** is now widely adopted by many applications, and
researchers have produced very dense literature on this topic. With the advent of smart …

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 …

The overall purpose of this paper is to provide an introductory survey in the area of
Simultaneous Localization and Map** (SLAM) particularly its utilization in autonomous …

Visual-inertial odometry (VIO) is the problem of estimating a robot's trajectory by combining
information from an inertial measurement unit (IMU) and a camera and is of great interest to …

In recent years, Simultaneous Localization And Map** (SLAM) technology has prevailed
in a wide range of applications, such as autonomous driving, intelligent robots, Augmented …

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 …

This paper explores the impact that landmark parametrization has in the performance of
monocular, EKF-based, 6-DOF simultaneous localization and map** (SLAM) in the …

This paper addresses the cooperative localization and visual map** problem with multiple
heterogeneous robots. The approach is designed to deal with the challenging large semi …

The main contribution of this paper is a novel feature parametrization based on parallax
angles for bundle adjustment (BA) in structure and motion estimation from monocular …

Most people believe SLAM is a complex nonlinear estimation/optimization problem.
However, recent research shows that some simple iterative methods based on linearization …