Simultaneous Localization and Mapping in dynamic en- vironments is an open issue in the field of robotics. Tra- ditionally, the related approaches assume that the environ- ment remains static during the robot's exploration phase. In this work, we overcome this assumption and propose an algorithm that exploits the dynamic nature of the environ- ment during robot exploration so as to improve the local- ization process. We use a Histogram Grid to store all the past occupancy values of every cell and thus to select the most probable pose of the robot based on the occupancy evolution. Experiments on a simulated robot indicate the effectiveness of the proposed approach.