We describe an approach to integrate dialogue management, machine-learning and action planning in a system for dialogue between a human and a robot. Case-based techniques are used because they permit life-long learning from experience and demand little prior knowledge and few static hand-written structures. This approach has been developed through the work on an experimental dialogue system, called CEDERIC, that is connected to an unmanned aerial vehicle (UAV). A single case base and case-based reasoning engine is used both for understanding and for planning actions by the UAV. Dialogue experiments both with experienced and novice users, where the users have solved tasks by dialogue with this system, showed very adequate success rates.