Simultaneous localization and map** (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

The number of research publications dealing with the simultaneous localization and
map** problem has grown significantly over the past 15 years. Many fundamental and …

Modern state estimation is often formulated as an optimization problem and solved using
efficient local search methods. These methods at best guarantee convergence to local …

In this article, we consider the problem of planar graph-based simultaneous localization and
map** (SLAM) that involves both poses of the autonomous agent and positions of …

We propose a scalable algorithm to take advantage of the separable structure of
simultaneous localization and map** (SLAM). Separability is an overlooked structure of …

The SLAM problem is known to have a special property that when robot orientation is
known, estimating the history of robot poses and feature locations can be posed as a …

This paper solves the classical problem of simultaneous localization and map** (SLAM) in
a fashion that avoids linearized approximations altogether. Based on the creation of virtual …

It is known that in the simultaneous localization and map** (SLAM) problem when a
robot's orientation is known, an estimation of the history of its poses can be formulated as a …

The simultaneous localization and map** (SLAM) problem has been a research focus for
many years and have reached a mature state. However, more robust solutions to the SLAM …

This paper compares two different objective functions in 2D point feature Simultaneous
Localization and Map** (SLAM). It is shown that the objective function can have a …