This paper shows and evaluates a novel approach to integrate a non-invasive Brain-Computer Interface (BCI) with the Robot Operating System (ROS) to mentally drive a telepresence robot. Controlling a mobile device by using human brain signals might improve the quality of life of people suffering from severe physical disabilities or elderly people who cannot move anymore. Thus, the BCI user can actively interact with relatives and friends located in different rooms thanks to a video streaming connection to the robot. To facilitate the control of the robot via BCI, we explore new ROS-based algorithms for navigation and obstacle avoidance in order to make the system safer and more reliable. In this regard, the robot exploits two maps of the environment, one for localization and one for navigation, and both are used as additional visual feedback for the BCI user to control the robot position. Experimental results show a decrease of the number of commands needed to complete the navigation task, suggesting a reduction user's cognitive workload. The novelty of this work is to provide a first evidence of an integration between BCI and ROS that can simplify and foster the development of software for BCI driven robotics devices.