An iterative approach for building feature maps in cyclic environments

In this paper we deal with one of the fundamen- tal problems for mobile robots, namely their ability to produce accurate representations of their environ- ment. We propose an oc e mapping algorithm that iteratively alternates between a Kalman smoother based localization step and a map features recalcu- lation step. Moreover, a hybrid algorithm with global localization capabilities is employed in the rst step, enabling correct identic ation of already mapped ar- eas, and, thus, ensuring map correctness in cyclic environments.