Explore the world's best driving roads on an interactive map. Discover hairpins, mountain passes, and flowing ridges scored near you and across the world.
Marker Monday: Antioch Potash Boom-Town - Nebraska State Historical Society
Our Historical Markers across Nebraska highlight fascinating moments and places in our state’s past. Today, we’re focusing on Antioch, the Nebraska ghost town that was once one of the most […]
Download Viking GPS data editor and analyzer for free. Viking is a free/open source program to manage GPS data. Viking is a free/open source program to manage GPS data. You can import, plot and create tracks, routes and waypoints, show OSM, Bing Aerial and other maps, geotag images, create routes using OSRM, see real-time GPS position (not in Windows), make maps using Mapnik (not in Windows), control items, etc.
The Wolfram Language has fully integrated capabilities for creating highly customized maps, as well as detailed built-in geographic information about all parts of the world. Maps in the Wolfram Language are defined both by geometric and graphical primitives, and by actual geographic entities, which can be entered using free-form linguistics.
Toggle navigation Home Download Screenshots Donate Contact Us Toggle navigation Home Download Screenshots Donate Contact Us Navit is free and without ads. Free maps based on OpenStreetMap. Disclaimer: OpenStreetMap is a trademark of the OpenStreetMap Foundation, and is used with their permission. This project is not endorsed by or affiliated...
Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. While this initially appears to be a chicken or the egg problem, there are several algorithms known to solve it in, at least approximately, tractable time for certain environments. Popular approximate solution methods include the particle filter, extended Kalman filter, covariance intersection, and GraphSLAM. SLAM algorithms are based on concepts in computational geometry and computer vision, and are used in robot navigation, robotic mapping and odometry for virtual reality or augmented reality.