Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine
learning techniques. The method is applied to the task of representing the tacit knowledge of a
trained camera assistant in minimally-invasive surgery. The model is then used for
intraoperative control of a robot that autonomously positions the endoscope. Furthermore a
modular robotics platform is described which forms the basis for this knowledge-based
assistance system. Promising results from a complex phantom study are presented.
