The Research Team "Automation and Robotics" deals with production planning and control, automation, and robotics. The group develops methods and tools for the design, simulation, and operation of machinery and facilities using virtual models. In addition, support for the development process is considered through appropriate mechatronic design and development systems. In the field of robotics, task-oriented methods and systems are investigated for the automated programming of industrial robots. In addition, the research team advises manufacturing companies on the introduction of RFID technology into production environments, for example, and consults on the implementation of technologies.

The focus areas of the Research Team "Automation and Robotics" include:

Robotics:  The main focus of the research work here is the development of robotic systems that can be quickly and seamlessly adapted to changing framework conditions, products, and processes in production environments. Methods and principles from robotics and other disciplines are combined and adapted to robotic systems. The focal points are the rapid and easy programming of industrial robots, the quick and safe interaction of industrial robots with humans, and the automatic calculation of robot paths.

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Control System Design and Simulation:  In this research field, the design and simulation of facilities play a central role as does the description of information interfaces. In this context, research is concerned with new concepts and their implementation in the automated generation of behavioral models for virtual operations. Thereby, new methods for control concepts are investigated. Research areas in system simulation require methods for semi-automated generation of physical models as well as the physically correct description of material flow behavior. Plug & Produce, the automated configuration of systems, represents our research goals in the area of information interfacing.

Cognitive Productions Systems: This research area is committed to the optimization and further development of production planning and control. The goals here are the integration of sensor networks into the production environment and the development of artificial cognitive systems. The Cognitive Factory is a paradigm in modern production science, where machines and facilities can perceive their environment and possess their own knowledge and planning ability as well as their own ability to learn from experiences. The development of such systems allows for quick and error-free adaptation to changing and unexpected situations, supports human-machine cooperation, and enables cost-effective production in turbulent environments. Hereby, methods of artificial intelligence (AI) are utilized and further developed, artificial cognitive systems are embedded in production environments, and sensor networks are utilized for the control and monitoring of production sequences.

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