Research

Real-world problems are often difficult to model in a small set of variables, which are needed to define a classical optimization problem. Inspired by human problem-solving abilities, wie explore heuristic strategies to problem-solving. [more information]

We propose a knowledge representation of everyday objects based on prototype theory in order to improve human-robot interaction. In AI objects are usually represented in the form of ontologies. Observations from psychology show that humans represent objects in a completely different way. Especially, the boundary between object classes is neither fixed nor can it easily be defined. In this project, which was funded by the ministry of science of Baden-Württemberg, we explore the use of prototype theory from psychology to represent everyday objects. Our test scenario is a kitchen, where our categorization algorithm has to store objects according to their functional and geometric properties, so that humans can easily find them. Doctoral Proposal of Alisa Volkert. [more information]

Robot path planning has traditionally concentrated on collision-free paths. For robots that collaborate closely with humans, however, the situation is different in two respects: 1) the humans in the robot's environment are not randomly moving objects, but cognitive beings who can deliberately make way for a robot to pass and 2) the quality of a navigation plan depends less on quantitative efficiency criteria, but rather on the acceptance of humans. We work on a robot navigation approach that takes into account human-centered requirements and the collaborative nature of the interaction between the human and the robot. [more information]