Academic Content & Certificates

The Cybernetics Lab conducts the academic content. Its interdisciplinary research focuses on information management, knowledge management, and management cybernetics.

In this Summer School, students receive an introduction to the engineering, controlling and programming of robots.

Future Industry: Networked, Distributed, Automated and Intelligent
Digitization changes the way in which industrial players design and manufacture products. One central goal is to overcome isolated solutions, which were created in the first phase of digitization, beginning around 1970. While the focus was on the determined optimization and digitization of individual process steps and within department boundaries, the goal during the current second phase of digitization is to achieve continuous networking, especially beyond boundaries of individual processes and departments. As a result, this networked architecture breaks down existing hierarchical information and control flows and replaces them by flexible, constantly changing networks of hardware and software services. The end of the information supply chain is characterized by robotized units, such as production machines and transport units, which are supplied with specific information for a flexible handling of their tasks – in an automated, autonomous, flexible and intelligent fashion.

Continuous and Process-Wide Information Acquisition and Supply
Communication is of tremendous importance in modern technical production systems. Nevertheless, because most of the factories constitute brown field environments and do represent grown structures, establishing communication between mostly heterogeneous systems is not an easy task. Without the right communication concept, future industrial solutions are not realizable. Thus, the first week of the summer school deals with the communication between heterogeneous systems in manufacturing. By starting with communication within technical systems, we discuss how to establish communication in production by modern means. We explore leading-edge communication protocols such as OPC UA as well as DDS and the students learn how to use these protocols within practical and hands-on modules.

Towards Intelligence: Self-Learning Industrial Robot
After understanding communications, we introduce industrial robots and talk about research challenges in this area. Students learn how to program and control robots using Linux and ROS (Robot Operating System). Further, the students get to know cutting-edge learning algorithms that allow robots to learn motion tasks via trial and error methods. This part involves a theoretical introduction to the principles of reinforcement learning and practical tasks. The students implement a learning algorithm for a real, continuous controlled robot and show the performance on an assembly task.

Multi-Robot System and High-Level Reasoning
Within future industry there is not one but thousands of robotic units working together. Therefore, the students learn about the most important aspects of a multi-robot system from perception to high-level reasoning guided by an example from the RoboCup Logistics League. The goal is to give an overview of the components of such a system and to provide practical experience in hands-on sessions. Students learn about our three-layered architecture for high-level decision-making. The lowest layer provides access to the robot hardware and implements basic components such as robot localization, navigation and perception. For the middle layer, we direct the students towards reactive behavior modelling. Finally, we talk about task-level reasoning and more specifically about the rule-based production system CLIPS. The students learn how rule-based production systems make decisions in general and perform practical implementations within hands-on sessions by using CLIPS.