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NRW Fortschrittskolleg: Gestaltung von flexiblen Arbeitswelten
(Arbeit 4.0)

T2 - Human-centered Cyber-Physical Devices

T2.1 Learning Assitance Systems

Learning assistance systems are designed to support a safe interaction between humans and complex technology by promoting the cognitive and physical performance of humans through the right balance of support and independence and adapting to the human being.  Examples are systems that, with new interaction technologies (e. g. gesture control, context-sensitive multi-modal user interfaces, interactive robots) and modern display technologies (e. g. active projections), allow for quick learning of assembly or machine operation, and in the production or assembly process for avoiding errors and thus improving safety as well as continuous process documentation. 

There is a considerable need for research into how the newly emerging roles and working methods with employees must be designed, how technologically the security and consistency of such interactive systems can be guaranteed, and how the interface between humans and systems can be designed in such a way that employees also feel subjectively secure and supported by the system, rather than being monitored or exploited.

The project can draw on preliminary work from industrial projects in which prototypes of such assistance systems were developed particularly with a focus on high process integration and stringent modelling in BPNM.

Contact person: Prof. Dr. Jochen J. Steil, Institute for Robotics and Process Control, TU Braunschweig, j.steil[at]

T2.2 Human Factors

The introduction and expansion of today's systems for human-CPS interaction will lead to significant changes in future industrial work that cannot yet be predicted in terms of their dimensions and effects for production and industrial service activities. Accordingly,  (further) developments of work-scientific approaches to research into the health burden and user acceptance of the changed human CPS collaborations are necessary. In this field of work, subjective perceptions (e. g. of safety) and an objective determination of the workload are to be investigated. In particular, this involves the automatic detection of signs of work-relevant emotional or cognitive states (such as fatigue, anger, surprise, uncertainty, etc.) and the development and evaluation of suitable models for the reaction to such detected states in a robot system in a specific task context.

Contact person: Prof. Dr. -Ing. Britta Wrede, CITEC, bwrede[at]techfak. uni-bielefeld. de, University of Bielefeld

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