Collaborative systems in which humans and robots share a common physical environment are part of the fourth industrial revolution. Since the health integrity of humans must not be compromised, collisions are often avoided by emergency stops of the machines, which in turn have a significant impact on the throughput of automated processes. By using motion predictions, a prospective navigation of robot movements emerges. In this paper, the benefits of such a human-robot system are evaluated. Recorded motion data of a human subject are used to simulate a quasi error-free motion prediction, which is integrated as a dynamic obstacle into the path planning of virtual robots. It is shown that a simple strategy significantly reduces safety risks, with only a minor impact on the throughput of the robots.