title: Visual EKF-SLAM from Heterogeneous Landmarks.
abstract: 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.
authors.affiliation: Center for Robotics and Intelligent Systems, Tecnológico de Monterrey, Monterrey 64849, Mexico. jo.esparza@itesm.mx.
authors.forename: Jorge Othón
authors.initials: JO
authors.lastname: Esparza-Jiménez
authors.affiliation: CNRS, LAAS, Université de Toulouse, 7 Avenue du Colonel Roche, Toulouse F-31400, France. michel.devy@laas.fr.
authors.forename: Michel
authors.initials: M
authors.lastname: Devy
authors.affiliation: Center for Robotics and Intelligent Systems, Tecnológico de Monterrey, Monterrey 64849, Mexico. jlgordillo@itesm.mx.
authors.forename: José L
authors.initials: JL
authors.lastname: Gordillo
keywords: EKF; SLAM; computer vision; landmarks; lines; points