Artificial Intelligence Review

, Volume 43, Issue 1, pp 55–81

Visual simultaneous localization and mapping: a survey


  • Jorge Fuentes-Pacheco
    • Centro Nacional de Investigación y Desarrollo Tecnológico
    • Centro Nacional de Investigación y Desarrollo Tecnológico
  • Juan Manuel Rendón-Mancha
    • Universidad Autónoma del Estado de Morelos

DOI: 10.1007/s10462-012-9365-8

Cite this article as:
Fuentes-Pacheco, J., Ruiz-Ascencio, J. & Rendón-Mancha, J.M. Artif Intell Rev (2015) 43: 55. doi:10.1007/s10462-012-9365-8


Visual SLAM (simultaneous localization and mapping) refers to the problem of using images, as the only source of external information, in order to establish the position of a robot, a vehicle, or a moving camera in an environment, and at the same time, construct a representation of the explored zone. SLAM is an essential task for the autonomy of a robot. Nowadays, the problem of SLAM is considered solved when range sensors such as lasers or sonar are used to built 2D maps of small static environments. However SLAM for dynamic, complex and large scale environments, using vision as the sole external sensor, is an active area of research. The computer vision techniques employed in visual SLAM, such as detection, description and matching of salient features, image recognition and retrieval, among others, are still susceptible of improvement. The objective of this article is to provide new researchers in the field of visual SLAM a brief and comprehensible review of the state-of-the-art.


Visual SLAMSalient feature selectionImage matchingData associationTopological and metric maps

Copyright information

© Springer Science+Business Media Dordrecht 2012