Real mobile robots should be able to build an abstract representation of the physical environment, in order to navigate and work in such environment. We propose a method for integrated exploration, where mobile robot incrementally build a map of this environment while simultaneously use this map to compute the absolute robot localization, and make local decisions on where to move next in order to minimize the error in the estimation of the mobile pose and the configuration locations. The continuous localization process is based on the extended Kalman filter. We present simulated and experimental results on the Pionner 3DX robot to show the performance of the proposed strategy. In this methodology the robot uses only range sensors.