Simultaneous Localization and Mapping (SLAM) is a technique used in robotics and computer vision that allows a device to create a map of an unknown environment while simultaneously keeping track of its own location within that environment. This is particularly useful for autonomous robots and vehicles that need to navigate without prior knowledge of their surroundings. SLAM combines data from various sensors, such as cameras and LIDAR, to identify landmarks and obstacles. By continuously updating its position and the map, the system can adapt to changes in the environment, making it essential for applications like self-driving cars and drones.