As changes in external environments are inevitable, a lifelong mapping system is desirable
for autonomous robots that aim at long-term operation. Capturing external environment …

As autonomous robots are increasingly being introduced in real-world environments
operating for long periods of time, the difficulties of long-term mapping are attracting the …

For autonomous vehicles to operate persistently in a typical urban environment, it is
essential to have high accuracy position information. This requires a mapping and …

Indoor SLAM and exploration is an important topic in robotics. Most solutions today work
with a 2D grid representation as map model, both for the internal data format and for the …

This work presents a semantic map management approach for various environments by
triggering multiple maps with different simultaneous localization and mapping (SLAM) …

The task of simultaneous localization and mapping (SLAM) is a widely studied field in
robotics research in the last decades. The goal of SLAM is to create an accurate map of the …

Maps are an important component of most robotic navigation systems and building maps
under uncertainty is often referred to as simultaneous localization and mapping or SLAM …

A Graph SLAM system is only as good as the edges in its pose graph. Critical mistakes in
the generation of these edges can instantly render a map inconsistent, misleading, and …

Localization and mapping are fundamental requirements to enable mobile robots to operate
robustly in their environments. The solution of these two problems will allow robots to assist …

Map building and localizing a robot within it are fundamental problems with autonomous
mobile robots. Simultaneous Localization and Mapping (SLAM) approaches aim to solve …