Visual EKF-SLAM from Heterogeneous Landmarks

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...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2016-04, Vol.16 (4), p.489-489
Main Authors: Esparza-Jiménez, Jorge Othón, Devy, Michel, Gordillo, José L
Format: Article
Language:English
Subjects:
Cameras
Computer Science
computer vision
Devices
EKF
Heterogeneity
Landmarks
lines
Localization
Optimization
points
Position (location)
Robotics
Robots
Sensors
SLAM
Visual
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s16040489