We present a robust method for automatically matching features in images corresponding to
the same physical point on an object seen from two arbitrary viewpoints. Unlike conventional …

Learning models of the environment is one of the fundamental tasks of mobile robots since
maps are needed for a wide range of robotic applications, such as navigation and …

A fast but nevertheless accurate approach for surface extraction from noisy 3D point clouds
is presented. It consists of two parts, namely a plane fitting and a polygonalization step. Both …

The Segway Robotic Mobility Platform (RMP) is a new mobile robotic platform based on the
self-balancing Segway Human Transporter (HT). The Segway RMP is faster, cheaper, and …

Learning maps is one of the fundamental tasks of mobile robots. In the past, numerous
efficient approaches to map learning have been proposed. Most of them, however, assume …

This paper is concerned with the Simultaneous Localization And Map** (SLAM) problem
using data obtained from a microwave radar sensor. The radar scanner is based on …

Most current navigation algorithms in mobile robotics produce 2D maps from data provided
by 2D sensors. In large part this is due to the availability of suitable 3D sensors and …

This paper presents a new approach for terrain map** and classification using mobile
robots with 2D laser range finders. Our algorithm generates 3D terrain maps and classifies …

In this research, we propose a method of SLAM in a dynamic large outdoor environment
using a laser scanner. Focus are cast on solving two major problems: 1) achieving global …

This paper describes an end-to-end system capable of generating high-quality 3D point
clouds from the popular LMS200 laser on a continuously moving platform. We describe the …