As robots are gradually leaving highly structured factory environments and moving into human populated environments, they need to possess more complex cognitive abilities. Not only do they have to operate efficiently and safely in natural populated environments, but also be able to achieve higher levels of cooperation and interaction with humans. The autonomous city explorer (ACE) project envisions to create a robot that will autonomously navigate in an unstructured urban environment and find its way through interaction with humans. To achieve this, research results from the fields of autonomous navigation, path planning, environment modeling, and human-robot interaction are combined. In this paper a novel hardware platform is introduced, a system overview is given, the research foci of ACE are highlighted, approaches to the occurring challenges are proposed and analyzed, and finally some first results are presented.