Lab for Machine Learning

Laboratory: Room 9.E.06 (Campus Konrad-Geiger)

Teaching

Final theses

On a regular basis, the lab offers to write internal final theses on current research topics. If you intend to write your Bachelor’s or Master’s thesis in the field of Machine Learning, please contact the corresponding lab manager.

Lab tests

Soon, the lab will also offer practical experiments and tests using the Horst 900 training system.

Focus topics of research and development

The focus topics of research at the Lab for Machine Learning lie in the following areas:

Robotics and machine learning in agriculture

Intelligent robots for agricultural applications bear great potential from economic and ecological standpoints. Automation can decrease costs and increase crop yield. Likewise, the use of crop protection products can be reduced. Possible applications for robots range from automated hoeing, mowing, and weed control to the detection of pest infestation or the degree of ripeness. Furthermore, pruning and harvest can be automated. For all of these steps, the robots require intelligent behaviour.

Robotics in intralogistics

The lab is currently working on solutions to use Reinforcement Learning for completing complex planning tasks. This enables robots to take on tasks formerly only fulfillable by humans. One of these planning tasks includes the packing of a stable dispatch pallet on which the space is used optimally by packaging items of different sizes.

Machine learning for electro-technical applications

Machine learning can be applied in various fields apart from robotics. The following topics have been addressed so far:

  • Anomaly detection and predictions for energy networks
  • Optimisation of e-machines by means of neural networks (it is possible to write a Master’s thesis on this topic!)
Image: A robot used in winegrowing
A robot used in winegrowing
Image: A robot packing a pallet of packages
A robot packing a pallet of packages

Equipment

  • Fruitcore Horst 900 training system
  • 6 student work stations (for Bachelor’s and Master’s theses)
  • Machine-Learning-Server (DELL system equipped with nVIDIA A100 cards)

Team

Name E-Mail Details
Gerald Barthelmes
Contact Information

Gerald Barthelmes

Technical University of Applied Sciences
Würzburg-Schweinfurt

Room 9.2.20
Konrad-Geiger-Straße 2
97421 Schweinfurt

Phone +49 9721 940-8647
E-Mail gerald.barthelmes[at]thws.de

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Fabian Dax
Contact Information

Fabian Dax

Technical University of Applied Sciences
Würzburg-Schweinfurt

Room 9.2.08
Konrad-Geiger-Straße 2
97421 Schweinfurt

Phone +49 9721 940-8691
E-Mail fabian.dax[at]thws.de

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Prof. Dr. Rainer Herrler
Contact Information

Prof. Dr. Rainer Herrler

Technical University of Applied Sciences
Würzburg-Schweinfurt

Room 9.1.04
Konrad-Geiger-Straße 2
97421 Schweinfurt

Phone +49 9721 940-8710
E-Mail rainer.herrler[at]thws.de

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