Active robot localization with macro actions

We propose a novel method for solving the localization problem, particularly useful in self-similar environments. Localization is the task of determining a robot's position with little or no prior knowledge about its initial location. We introduce a computationally efficient active strategy for the localization task. The proposed method also automatically generates optimal macro actions giving the robot the ability to localize in all environments. Combining the active strategy and macro actions, the method introduces an efficient strategy for determining a robot's position in any environment where localization is possible.