A robot moving through an unfamiliar building must build a picture of its surroundings and work out where it sits within them at the same time. Solving both problems together from camera images is known as SLAM, short for simultaneous localization and mapping. The cameras used here record a normal colour image together with the distance to everything in view; such devices are called depth cameras, or RGB-D cameras, and they suit indoor robots because they provide both appearance and scale without the cost of a laser scanner. Many open-source SLAM systems exist, and they differ considerably in how they store the map, how they recognize a place already visited, how much computing power they require, and how well they cope with dim light or rapid motion.