VSLAM
Visual Simultaneous Localization and Mapping, commonly known as VSLAM, is a technology that allows a robot or device to build a map of an unknown environment while simultaneously tracking its own position within that map. This is achieved by using cameras as the primary sensors. VSLAM systems typically analyze video streams from one or more cameras to identify distinctive features in the environment. By observing how these features move across different camera frames, the system can infer both the camera's motion (localization) and the three-dimensional structure of the surroundings (mapping).
The core process involves feature detection and matching. Features can be corners, edges, or more complex textured
VSLAM has applications in a wide range of fields, including autonomous navigation for robots, augmented reality