Mobile robots that are deployed, for instance, for domestic tasks, need to fulfill them even if they do not have complete information about the domain beforehand. Consider, for example, the task of fetching an object from a specific room. Consider further that the robot has a map of the environment and that it can plan a path to the living room. However, only when reaching the door of the living room, it will know whether or not the door is open. Moreover, it might not be known where in the living room the object is located such that the robot needs to make a plan how to find it. Next, a plan for grabbing the object in a safe way is required. This includes taking camera shots from different angles and finding an appropriate location to grab the object. Basically, the action control of the robot continuously needs to combine active perception and high-level planning with action execution. The robot has to deal with qualitative action and world descriptions as well as with uncertainty and quantitative data from sensors and actuators. The objective of this project is to develop methods for solving tasks like the above in an intelligent way by combining perception, high-level planning and action execution. An evaluation of the developed methods will be conducted on existing mobile robotic platforms.