Cross-faculty Research Area for Robotics and Artificial Intelligence
About the laboratory
The Cross-faculty Research Area for Robotics and AI is located on the new HKA2030+ Campus / TP (Technology Park) and is used for research and development of robot-based solutions for production and distribution logistics. The lab is equipped with modern infrastructure as well as mobile and stationary state-of-the-art robots from KUKA and Universal Robots.
The laboratory is used for teaching by the Faculty of Mechanical Engineering and Mechatronics, the Faculty of Management Science and Engineering, the Faculty of Electrical Engineering and Information Technology and the Faculty of Computer Science and Business Information Systems as well as for research by the Institute of Applied Research
Agile development of gripping systems and other components is implemented in numerous research projects in collaboration with the Additive Design and Manufacturing Lab (ADM-Lab). Feasibility studies and cooperative research projects with industry and research partners can be carried out in the lab.
Technical equipment
Our research area features several stationary robot cells with robots from KUKA and Universal Robots. The portfolio is supplemented by several mobile robot systems from Neobotix, Scitos and KUKA. Most of the robot systems are equipped with gripping systems from Schunk, Zimmer and Schmalz as well as with camera and image processing systems from RoboCeption, Cognex, Helios and Intel.
The programming of the robot systems is partly realized via the respective manufacturer-specific languages. Some systems use the Robot Programming Suite (RPS) from Artiminds or the drag&bot OS from Drag & Bot GmbH. In most research projects, the robot systems are programmed with the open source framework ROS2.
In the field of robot simulation, the laboratory is equipped with 60 KUKA.Sim licenses.
For image processing, standard software systems such as MVTec HALCON and Cognex VisionPro are used as well as self-developed systems based on open source frameworks such as OpenCV and TensorFlow (Deep Learning).
Research and Teaching
Research projects currently ongoing in the research area include the following main topics:
- Development of a synthetic data generation and training pipeline for AI-based machine vision systems in industrial applications (e.g. SyDaVis-AI project)
- Visualization of deep neural networks (e.g. QualiTED project)
- Development of an Autonomous, mobile system for intelligent linking of production workstations with transport-parallel quality assurance (e.g. QualiTEDproject)
- Developing AI-enabled infrastructures for university-wide deployment (e.g. ILKA project)
