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Journal of Sensors
Volume 2017 (2017), Article ID 3497650, 20 pages
https://doi.org/10.1155/2017/3497650
Review Article

A State-of-the-Art Review on Mapping and Localization of Mobile Robots Using Omnidirectional Vision Sensors

Universidad Miguel Hernández de Elche, Avda. de la Universidad s/n, Elche, Spain

Correspondence should be addressed to O. Reinoso; se.hmu.hmuog@osonier.o

Received 19 October 2016; Revised 19 February 2017; Accepted 15 March 2017; Published 24 April 2017

Academic Editor: Lucio Pancheri

Copyright © 2017 L. Payá et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Nowadays, the field of mobile robotics is experiencing a quick evolution, and a variety of autonomous vehicles is available to solve different tasks. The advances in computer vision have led to a substantial increase in the use of cameras as the main sensors in mobile robots. They can be used as the only source of information or in combination with other sensors such as odometry or laser. Among vision systems, omnidirectional sensors stand out due to the richness of the information they provide the robot with, and an increasing number of works about them have been published over the last few years, leading to a wide variety of frameworks. In this review, some of the most important works are analysed. One of the key problems the scientific community is addressing currently is the improvement of the autonomy of mobile robots. To this end, building robust models of the environment and solving the localization and navigation problems are three important abilities that any mobile robot must have. Taking it into account, the review concentrates on these problems; how researchers have addressed them by means of omnidirectional vision; the main frameworks they have proposed; and how they have evolved in recent years.