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Article Dans Une Revue Sensors Année : 2016

Visual EKF-SLAM from Heterogeneous Landmarks

Résumé

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.
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Dates et versions

hal-01354880 , version 1 (19-08-2016)

Identifiants

Citer

Jorge Esparza-Jiménez, Michel Devy, José Gordillo. Visual EKF-SLAM from Heterogeneous Landmarks. Sensors, 2016, 16 (4), ⟨10.3390/s16040489⟩. ⟨hal-01354880⟩
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