We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loopclosure detection method based on bags of visual words which is able to detect when the robot has returned back to a previously visited place. An efficient optimization algorithm is used to integrate odometry information in this method to generate a consistent topo-metrical map. The resulting algorithm which only requires a monocular camera and odometry data and is simple, and robust without requiring any a priori information on the environment.