We study how a mobile robot can piecemeal learn an unknown environment. The robot's goal is to learn a complete map of its environment, while satisfying the constraint that it must return every so often to its starting position (for refueling, say). The environment is modelled as an arbitrary, undirected graph, which is initially unknown to the robot.
