The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A new method for efficiently mapping three dimensional environments from a platform carrying a single calibrated camera, and simultaneously localizing the platform within this map is presented in this paper. This is the Monocular SLAM problem in robotics, which is equivalent to the problem of extracting Structure from Motion (SFM) in computer vision. A novel formulation of Monocular SLAM which exploits...
This paper addresses the problem of mapping three dimensional environments from a sequence of images taken by a calibrated camera, and simultaneously generating the camera motion trajectory. This is the Monocular SLAM problem in robotics, and is akin to the Structure from Motion (SFM) problem in computer vision. We present a novel map-aided 6-DOF relative pose estimation method based on a new formulation...
This paper presents a new technique for evaluating the observability of the simultaneous localization and mapping (SLAM) problem. The state vector of an estimation theoretic formulation of the SLAM problem is recast to include all robot poses from which the measurements are made. This converts SLAM to a problem of estimating a set of unknown, constant random variables. Fisher Information Matrix of...
This paper presents a novel local submap joining algorithm for building large-scale feature-based maps: sparse local submap joining filter (SLSJF). The input to the filter is a sequence of local submaps. Each local submap is represented in a coordinate frame defined by the robot pose at which the map is initiated. The local submap state vector consists of the positions of all the local features and...
This paper presents an algorithm for the multi-robot simultaneous localization and mapping (SLAM) problem with the robot initial locations completely unknown. Each robot builds its own local map using the traditional extended Kalman filter (EKF) SLAM algorithm. We provide a new method to fuse the local maps into a jointly maintained global map by first transforming the local map state estimate into...
The main contribution of this paper is a new SLAM algorithm for the mapping of large scale environments by combining local maps. The local maps can be generated by traditional extended Kalman filter (EKF) based SLAM. Relationships between the locations of the landmarks in the local map are then extracted and used in an extended information filter (EIF) to build a global map. An important feature is...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.