In the RoboCup@Home domestic robot competition, complex tasks such as ``get the cup from the kitchen and bring it to the living room'' or ``find me this and that object in the apartment'' have to be accomplished. At these competitions the robots may only be instructed by natural language. As humans use qualitative concepts such as ``near'' or ``far'', the robot needs to cope with them, too. For our domestic robot, we use the robot programming and plan language Readylog, our variant of Golog. In previous work we extended the action language Golog, which was developed for the high-level control of agents and robots, with fuzzy concepts and showed how to embed fuzzy controllers in Golog. In this paper, we demonstrate how these notions can be fruitfully applied to two Robocup@Home scenarios. In the first application, we demonstrate how qualitative fluents based on a fuzzy set semantics can be deployed. In the second program, we show an example of a fuzzy controller for a follow-a-person task. While these programs have to be regarded as a proof-of-concept for the possibility to integrate qualitative concepts into Readylog beneficially for such applications, we aim at implementing these programs on our domestic robot platform in the future.