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 complete approach to the visual localization and mapping problem (SLAM) is presented in this work. The presented approach exploits the enhanced capabilities of a system where a human and a robot collaborate in surveying/exploratory tasks. The human is supposed to wear a smart headwear device, which deploys a inertial measurement unit and a camera, Hv. This camera acts as a secondary sensor, and...
A novel approach to the SLAM problem has been tested in an industrial environment within a robotic assistance context. In order to be fully reliable in non-modelled circumstances where the environment cannot be considered as known a priori, a robot assistant must be able to localize and map its environment. The use of a camera sensor to solve localization has several advantages and weaknesses due...
Simultaneous Localization and Mapping (SLAM) is perhaps the most fundamental problem to solve in robotics in order to build truly autonomous mobile robots. The sensors have a large impact on the algorithm used for SLAM. In this work a novel method, called Filtered Inverse Depth Delayed (FIDD) Initialization which is intended for initializing new features in Bearing-Only SLAM systems. Unlike range...
The on-line robot estimation position from measurements of self-mapped features is a class of problem called, in the robotics community, as simultaneous localization and mapping (SLAM) problem, which is one of the fundamental problems in robotics. SLAM consists in incrementally building a consistent map of the environment and, at the same time, localizing the position of the robot while it explores...
Cameras have gained a great interest as sensors for the robotic research community, because they yield a lot of information. Cameras are well adapted for embedded systems; they are light, cheap and power saving. As the computational power grows, an inexpensive camera can be used to perform range and appearance-based sensing simultaneously, replacing typical sensors as laser and sonar rings for range...
The ego-motion online estimation process from a video input is often called visual odometry. Typically optical flow and structure from motion (SFM) techniques have been used for visual odometry. Monocular simultaneous localization and mapping (SLAM) techniques implicitly estimate camera ego-motion while incrementally build a map of the environment. However in monocular SLAM, when the number of features...
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.