About us

Augmented Reality

Augmented Reality is used in a wide range of logistics processes, such as incoming goods or picking. During the picking process, the employee receives specific product information via special data glasses where the storage location can be visually displayed. The Fraunhofer IML has been researching for many years in the field of AR and developed, for example, a system that improves packaging processes using data glasses. Here, the employee is guided through the process and is shown at which point the product should be optimally placed.

AR - Visual - Individual

The use of AR technologies is not limited to the classic AR glasses, but also works well with a smartphone or tablet. Depending on the field of application, AR can be used in various ways. The use of the three-dimensional representation of objects is not always necessary. For maintenance work, it may e.g. suffice that simple texts are projected to the respective machines in the field of view of the employee. On this basis, Fraunhofer IML develops flexible and individual solutions for your processes.

AR - increasing usability

AR optimally supports employees in their work. Important information about the location of machines or approaching vehicles leads to the safe handling of complex systems. In addition, they will be shown the best way through the warehouse to the respective products. But also, in the field of repair, AR enables a simplified handling. Thus, for example, the maintenance plans and additional design data can be projected into the field of view of the worker.

Automated guided vehicles

Automated guided vehicles (AGV) or mobile robots support employees in manual processes in a wide variety of areas. We have many years of experience in the development of such systems. The developed transport vehicles act completely autonomously and can interact with their environment and humans. They can be controlled via conventional HMI as well as via smartwatches and AR goggles. The inclusion of the transported goods can be done depending on the particular application by means of active and passive load handling devices. Subsequently, the AGV can transfer the loads to corresponding systems at different heights and thereby also position the load ergonomically favorable for humans. For movement, the vehicle can be equipped with a laser navigation. In this case, the current vehicle position can be determined by the measurements of the attached laser sensors. Other navigation methods such as optical tracking may also be suitable depending on the application.

Machine Learning

Artificial Intelligence (AI) is one of the hopefuls for Germany as an industrial location. As a subfield of AI, machine learning is successful wherever processing a large amount of data poses a challenge to a human, so engineering does not accomplish the goal. This is especially true for image data, for example in autonomous vehicles, where automatic detection can be life-saving support to the driver. Other examples are human language communication, event prediction or optimization of processes. In logistics, the application possibilities are various. Autonomous vehicles can tell whether they are crossing the road with a human or if they have a pallet in front of them. Systems can autonomously assess their degree of wear or detect damage before adverse effects occur or regular maintenance is performed.

In addition to these applications, Fraunhofer IML is also researching more fundamental questions. One current hurdle for the use of machine learning is the computational power required, usually provided by powerful graphics cards or special processors. This leads to high costs and excessive energy consumption, which is particularly problematic in mobile robotics. Various solution strategies are promising, such as the use of NVIDIA embedded systems, like EMILI, or the development of algorithms capable of abandoning common frameworks by automatically translating the learned models into executables adapted to the target platform.

IoT Devices

Designing integrated embedded systems, from board design to software development for microcontrollers and digital signal processors, creates small and cost-effective automation solutions. By using the latest technologies, we develop miniaturized, lean systems and thus generate competitive advantages for you. For example, the latest developments can ensure long-term localization and monitoring of goods. In addition, the built-in sensors allow movement data and temperature of the goods to be measured. The use of energy-saving and cost-effective technologies paves the way for large-scale deployment in companies from a wide variety of industries.

Head of Department


Dr.-Ing. Sören Kerner


Phone  +49 231 9743-170

Fax +49 231 9743-77170


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Team Members


Leonie Benkenstein, B.Sc.

Phone +49 231 9743-474



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Tobias Bich, M.Sc.


Phone +49 231 9743-138



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Dr.-Ing. Marius Brehler


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Peter Detzner, M.Sc.


Phone +49 231 9743-325

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Dipl.-Inform. Jan Sören Emmerich

Phone +49 231 9743-526



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Jan Finke, M.Sc.


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Julian Eßer, M.Sc.





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Ulrich Franzke


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Christian Hammermeister, M.Sc.

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Dipl.-Inf. Dirk Höning


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Sebastian Hoose, M.Sc.





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Christian Jestel, M.Sc.





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Jana Jost, M.Sc.


Phone +49 231 9743-522



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Sönke Kauffmann, M.Sc.


Phone +49 231 9743-438



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Thomas Kirks, M.Eng.


Phone +49 231 9743-134

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Dennis Lünsch, M.Sc.


Phone +49 231 9743-519



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Fabian Menebröker, M.Sc.

Phone +49 231 9743-327

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Tobias Naumann, M.Sc.


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Volkmar Pontow


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Aswin Karthik Ramachandran Venkatapathy, M.Sc.

Phone +49 231 9743-517


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Andreas Riesner, B.Sc.


Phone +49 231 9743-512



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David Ronnenberg, M.Sc.





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Philipp Schulte, M.Sc.





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Leon Valentin Siebel-Achenbach, B.Eng.

Phone +49 231 9743-432



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Jonas Stenzel, M.Sc.


Phone +49 231 9743-118

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Dr.-Ing. Oliver Urbann


Phone +49 231 9743-547

Fax +49 231 9743-77547


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