Dr.-Ing.

Gruna, Robin

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  • Publication
    SmartSpectrometer - Embedded Optical Spectroscopy for Applications in Agriculture and Industry
    ( 2021)
    Krause, Julius
    ;
    Grüger, Heinrich
    ;
    Gebauer, Lucie
    ;
    Zheng, Xiaorong
    ;
    Knobbe, Jens
    ;
    Pügner, Tino
    ;
    Kicherer, Anna
    ;
    Gruna, Robin
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be acquired and evaluated in real time, and the results can be integrated directly into process and automation units, saving resources and costs. Multivariate data analysis is needed to integrate optical spectrometers as sensors. Therefore, a spectrometer with integrated artificial intelligence (AI) called SmartSpectrometer and its interface is presented. The advantages of the SmartSpectrometer are exemplified by its integration into a harvesting vehicle, where quality is determined by predicting sugar and acid in grapes in the field.
  • Publication
    Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking
    ( 2021)
    Maier, Georg
    ;
    Pfaff, Florian
    ;
    Pieper, Christoph
    ;
    Gruna, Robin
    ;
    Noack, Benjamin
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    Kruggel-Emden, Harald
    ;
    Längle, Thomas
    ;
    Hanebeck, Uwe D.
    ;
    Wirtz, Siegmar
    ;
    Scherer, Viktor
    ;
    Beyerer, Jürgen
    Sensor-based sorting is a machine vision application that has found industrial application in various fields. An accept-or-reject task is executed by separating a material stream into two fractions. Current systems use line-scanning sensors, which is convenient as the material is perceived during transportation. However, line-scanning sensors yield a single observation of each object and no information about their movement. Due to a delay between localization and separation, assumptions regarding the location and point in time for separation need to be made based on the prior localization. Hence, it is necessary to ensure that all objects are transported at uniform velocities. This is often a complex and costly solution. In this paper, we propose a new method for reliably separating particles at non-uniform velocities. The problem is transferred from a mechanical to an algorithmic level. Our novel advanced image processing approach includes equipping the sorter with an area-scan camera in combination with a real-time multiobject tracking system, which enables predictions of the location of individual objects for separation. For the experimental validation of our approach, we present a modular sorting system, which allows comparing sorting results using a line-scan and area-scan camera. Results show that our approach performs reliable separation and hence increases sorting efficiency.
  • Publication
    From Visual Spectrum to Millimeter Wave: A Broad Spectrum of Solutions for Food Inspection
    ( 2020)
    Becker, Florian
    ;
    Schwabig, Christopher
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    Krause, Julius
    ;
    Leuchs, Sven
    ;
    Krebs, Christian
    ;
    Gruna, Robin
    ;
    Kuter, Andries
    ;
    Längle, Thomas
    ;
    Nußler, Dirk
    ;
    Beyerer, Jürgen
    The consequences of food adulteration can be far reaching. In the past, inexpensive adulterants were used to inflate different products, leading to severe health issues. Contamination of food has many causes and can be physical(plant stems in tea), chemical (melamine in infant formula), or biological (bacterial contamination). Employing suitable sensor systems along the production process is a requirement for food safety. In this article, different approaches to food inspection are illustrated, and exemplary scenarios outline the potential of different sensor systems along the spectrum.