Combining Odometry and Visual Loop‐Closure Detection for Consistent Topo‐Metrical Mapping

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 loop‐closure detection method based on bags of visual words (2008), 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 and to generate a consistent topo‐metrical map much more usable for global localization and path planning. The resulting algorithm which only requires a monocular camera and robot odometry data, is real‐time, incremental (i.e. it does not require any a priori information on the environment), and can be easily embedded on medium platforms.