This paper presents an approach to reduce the technical complexity of a service robotic system by means of systematic and well-balanced user-involvement. By taking advantage of the user's cognitive capabilities during task execution, a technically manageable robotic system, which is able to execute tasks on a high level of abstraction reliably and robustly, emerges. For the realisation of this approach, the control architecture MASSiVE has been implemented, which is used for the control of the rehabilitation robot FRIEND II. It supports task execution on the basis of a priori defined and formally verified task-knowledge. This task-knowledge contains all possible sequences of operations as well as the symbolic representation of objects required for the execution of a specific task. The seamless integration of user interactions into this task-knowledge, in combination with MASSiVE's user-adapted human–machine interface layer, enables the system to deliberately interact with the user during run-time.