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Sensors 2016, 16(4), 489;

Visual EKF-SLAM from Heterogeneous Landmarks

Center for Robotics and Intelligent Systems, Tecnológico de Monterrey, Monterrey 64849, Mexico
CNRS, LAAS, Université de Toulouse, 7 Avenue du Colonel Roche, Toulouse F-31400, France
This paper is an extended version of our paper published in Esparza-Jimenez, J.O.; Devy, M.; Gordillo, J.L. EKF-based SLAM fusing heterogeneous landmarks. In Proceedings of the IEEE 2014 17th International Conference on Information Fusion (FUSION), Salamanca, Spain, 7–10 July 2014; pp. 1–8
These authors contributed equally to this paper.
Author to whom correspondence should be addressed.
Academic Editors: Lianqing Liu and Yajing Shen
Received: 31 December 2015 / Revised: 24 March 2016 / Accepted: 30 March 2016 / Published: 7 April 2016
(This article belongs to the Special Issue Sensors for Robots)
Full-Text   |   PDF [6165 KB, uploaded 7 April 2016]   |  


Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology. View Full-Text
Keywords: SLAM; EKF; computer vision; landmarks; points; lines SLAM; EKF; computer vision; landmarks; points; lines

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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. (CC BY 4.0).

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Esparza-Jiménez, J.O.; Devy, M.; Gordillo, J.L. Visual EKF-SLAM from Heterogeneous Landmarks. Sensors 2016, 16, 489.

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