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.
In this paper a Hardware Architecture for computing the Extended Kalman Filter (EKF) is presented which is addressed to solve the self-localization problem of autonomous mobile robots. In this case, the overall EKF algorithm has been implemented in hardware over an Altera Cyclone IV FPGA with a Nios II processor, in which the latter is used only for interfacing and communication tasks. The achieved...
This work presents an FPGA-based Hardware Architecture to implement the Prediction Stage of the Extended Kalman Filter (EKF) applied to the localization problem in mobile robotics. The algorithm has been implemented and run on an Altera Cyclone IV FPGA with a Nios II processor, being adapted and applied to the mobile platform Pioneer 3AT (P3AT). The prediction stage was based on a dead-reckoning system...
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.