Brain activity recorded non-invasively is sufficient to control a moblie robot if advanced robotics is used in combination with asynchronous EEG analysis and machine learning techniques. Until now brain-actuated control has mainly relied on implanted electrodes, since EEG based systems have bben considered tto slow for controlling rapid and complex sequences of movements. We show that two human subjects successfully moved a robot between several rooms by mental control only using an EEG based brain-machine interface that recognized three mental states. Mental control was comparable to manual control on the same task with a preformance ration of 0.74.