SLAM

Simultaneous Localization and Mapping — the problem of building a map of an unknown environment while simultaneously tracking the robot's position within it. SLAM is a chicken-and-egg problem: you need a map to localize, and you need localization to build a map. It is solved through probabilistic estimation (filtering or graph optimization). SLAM is fundamental to autonomous mobile robotics.