Visual EKF-SLAM from Heterogeneous Landmarks†
AbstractMany 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
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Esparza-Jiménez, J.O.; Devy, M.; Gordillo, J.L. Visual EKF-SLAM from Heterogeneous Landmarks. Sensors 2016, 16, 489.
Esparza-Jiménez JO, Devy M, Gordillo JL. Visual EKF-SLAM from Heterogeneous Landmarks. Sensors. 2016; 16(4):489.Chicago/Turabian Style
Esparza-Jiménez, Jorge O.; Devy, Michel; Gordillo, José L. 2016. "Visual EKF-SLAM from Heterogeneous Landmarks." Sensors 16, no. 4: 489.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.