Learning and Utilizing Spatial Object Relations for Service Robots Learning and Utilizing Spatial Object Relations for Service Robots

Service robots that operate in domestic environments and assist in the daily housework are still beyond reach when considering the current state of the art. Hence, they pose many inte-resting technical challenges that currently motivate a considerable amount of basic research in mobile robotics. One of these challenges is the question how service robots could attain the required level of autonomy and reliability to be truly useful. Ideally, if a service robot is deployed in a domestic environment it should require only a short setup time and as few user interactions as possible. When tidying up, it should know where the objects usually belong to. If the robot should set the table, it needs to know which objects are required, where to find them, and how they should be arranged on the table. It is apparent that most of these tasks involve knowledge about the spatial context of objects and how objects are usually arranged in such environments. It would be desirable to have a flexible approach in which the robot adapts to the specifics of its environment by observing it. It thereby could learn the usual object arrangements. Hence, as a basic requirement for achieving a high level of autonomy, service robots need to represent, learn, and utilize knowledge about th