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Visual simultaneous localization and mapping: a survey

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Abstract

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.

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Authors and Affiliations

  1. Centro Nacional de Investigación y Desarrollo Tecnológico, Cuernavaca, Morelos, México

    Jorge Fuentes-Pacheco & José Ruiz-Ascencio

  2. Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, México

    Juan Manuel Rendón-Mancha

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  1. Jorge Fuentes-Pacheco
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  2. José Ruiz-Ascencio
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  3. Juan Manuel Rendón-Mancha
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Correspondence to José Ruiz-Ascencio.

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Fuentes-Pacheco, J., Ruiz-Ascencio, J. & Rendón-Mancha, J.M. Visual simultaneous localization and mapping: a survey. Artif Intell Rev 43, 55–81 (2015). https://doi.org/10.1007/s10462-012-9365-8

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