While a group of mobile robots carry out a task, they need to find their location within the environment. In consequence a precise map of a general and undetermined environment has to be known by the robots. During the last decade a series of methods have been developed that allow the construction of the map by a mobile robot. These algorithms consider the case in which the vehicle moves along the environment, constructs the map while, simultaneously, computes its location within the map. As a result, this problem has been named Simultaneous Localization and Mapping (SLAM). This research project focusses thus on the construction of visual maps in 3D general unknown environments by using a team of mobile robots equipped with vision sensors. In this sense, we propose to undertake, among others, the following lines: 6 DOF cooperative visual SLAM, in which the robots move following general trajectories in the environment (with 6 degrees of freedom) instead of the classical trajectories in which it is assumed that the robots navigates on a two-dimensional plane; integrated exploration, where the exploration paths of the robots consider to maximize the knowledge of the environment and, at the same time, take into account the uncertainty in the maps created by the robot(s); map alginment and map fusion of local maps created by different robots; and finally, the creation of maps using the information based in the visual appearance that allows the construction of high-level topological maps.