Dr.-Ing.

Gruna, Robin

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  • Publication
    Real-time multitarget tracking for sensor-based sorting: A new implementation of the auction algorithm for graphics processing units
    ( 2019)
    Maier, Georg
    ;
    Pfaff, F.
    ;
    Wagner, M.
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    Pieper, C.
    ;
    Gruna, Robin
    ;
    Noack, B.
    ;
    Kruggel-Emden, H.
    ;
    Längle, Thomas
    ;
    Hanebeck, U.D.
    ;
    Scherer, V.
    ;
    Beyerer, Jürgen
    Utilizing parallel algorithms is an established way of increasing performance in systems that are bound to real-time restrictions. Sensor-based sorting is a machine vision application for which firm real-time requirements need to be respected in order to reliably remove potentially harmful entities from a material feed. Recently, employing a predictive tracking approach using multitarget tracking in order to decrease the error in the physical separation in optical sorting has been proposed. For implementations that use hard associations between measurements and tracks, a linear assignment problem has to be solved for each frame recorded by a camera. The auction algorithm can be utilized for this purpose, which also has the advantage of being well suited for parallel architectures. In this paper, an improved implementation of this algorithm for a graphics processing unit (GPU) is presented. The resulting algorithm is implemented in both an OpenCL and a CUDA based environment. By using an optimized data structure, the presented algorithm outperforms recently proposed implementations in terms of speed while retaining the quality of output of the algorithm. Furthermore, memory requirements are significantly decreased, which is important for embedded systems. Experimental results are provided for two different GPUs and six datasets. It is shown that the proposed approach is of particular interest for applications dealing with comparatively large problem sizes.
  • Publication
    Application of area-scan sensors in sensor-based sorting
    ( 2018)
    Maier, Georg
    ;
    Pfaff, F.
    ;
    Pieper, C.
    ;
    Gruna, Robin
    ;
    Noack, B.
    ;
    Kruggel-Emden, H.
    ;
    Längle, Thomas
    ;
    Hanebeck, U.D.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    ;
    Beyerer, Jürgen
    In the field of machine vision, sensor-based sorting is an important real-time application that enables the separation of a material feed into different classes. While state-of-the-art systems utilize scanning sensors such as line-scan cameras, advances in sensor technology have made application of area scanning sensors feasible. Provided a sufficiently high frame rate, objects can be observed at multiple points in time. By applying multiobject tracking, information about the objects contained in the material stream can be fused over time. Based on this information, our approach further allows predicting the position of each object for future points in time. While conventional systems typically apply a global, rather simple motion model, our approach includes an individual motion model for each object, which in turn allows estimating the point in time as well as the position when reaching the separation stage. In this contribution, we present results from our collaborative research project and summarize the present advances by discussing the potential of the application of area-scan sensors for sensor-based sorting. Among others, we introduce our simulation-driven approach and present results for physical separation efficiency for simulation-generated data, demonstrate the potential of using motion-based features for material classification and discuss real-time related challenges.
  • Publication
    Numerical modelling of an optical belt sorter using a DEM-CFD approach coupled with particle tracking and comparison with experiments
    ( 2018)
    Pieper, C.
    ;
    Pfaff, F.
    ;
    Maier, Georg
    ;
    Kruggel-Emden, H.
    ;
    Wirtz, S.
    ;
    Noack, B.
    ;
    Gruna, Robin
    ;
    Scherer, V.
    ;
    Hanebeck, U.D.
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    State-of-the-art optical sorting systems suffer from delays between the particle detection and separation stage, during which the material movement is not accounted for. Commonly line scan cameras, using simple assumptions to predict the future particle movement, are employed. In this study, a novel prediction approach is presented, where an area scan camera records the particle movement over multiple time steps and a tracking algorithm is used to reconstruct the corresponding paths to determine the time and position at which the material reaches the separation stage. In order to assess the benefit of such a model at different operating parameters, an automated optical belt sorter is numerically modelled and coupled with the tracking procedure. The Discrete Element Method (DEM) is used to describe the particle-particle as well as particle-wall interactions, while the air nozzles required for deflecting undesired material fractions are described with Computational Fluid Dynamics (CFD). The accuracy of the employed numerical approach is ensured by comparing the separation results of a predefined sorting task with experimental investigations. The quality of the aforementioned prediction models is compared when utilizing different belt lengths, nozzle activation durations, particle types, sampling frequencies and detection windows. Results show that the numerical model of the optical belt sorter is able to accurately describe the sorting system and is suitable for detailed investigation of various operational parameters. The proposed tracking prediction model was found to be superior to the common line scan camera method in all investigated scenarios. Its advantage is especially profound when difficult sorting conditions, e.g. short conveyor belt lengths or uncooperative moving bulk solids, apply.
  • Publication
    Motion-based material characterization in sensor-based sorting
    ( 2018)
    Maier, Georg
    ;
    Pfaff, F.
    ;
    Becker, F.
    ;
    Pieper, C.
    ;
    Gruna, Robin
    ;
    Noack, B.
    ;
    Kruggel-Emden, H.
    ;
    Längle, Thomas
    ;
    Hanebeck, U.D.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    ;
    Beyerer, Jürgen
    Für die Sortierung von kohäsiven, granularen Materialien entspricht die sensorgestützte Sortierung dem Stand der Technik. Die Auswahl geeigneter Systemkomponenten, wie etwa Sensorik, Beleuchtung, oder die Realisierung der Datenauswertung, orientiert sich bei der Entwicklung entsprechender Systeme an der konkreten Sortieraufgabe, die es zu lösen gilt. Eine Gemeinsamkeit findet sich im Einsatz scannender Sensoren. Jüngst wurde jedoch der Einsatz von Flächenkameras vorgeschlagen. Durch die Beobachtung von Objekten zu mehreren Zeitpunkten besteht die Möglichkeit, deren Bewegungspfade zu verfolgen. Dies erlaubt eine präzise Schätzung der Position und des Zeitpunkts, zu welchem ein Objekt die Trennstufe des Systems erreicht und hilft somit dabei, den Fehler in der physikalischen Separation zu verringern. In dieser Veröffentlichung wird vorgeschlagen, diese Bewegungsinformation ebenfalls zur Charakterisierung von Materialien zu verwenden. Durch die Ableitung geeigneter Merkmale zeigen wir exemplarisch für eine Klassifikationsaufgabe, dass hierdurch gute Ergebnisse erzielt werden können. Der vorgestellte Ansatz trägt damit zur Verringerung des Erkennungsfehlers in Sortiersystemen bei.
  • Publication
    Improving multitarget tracking using orientation estimates for sorting bulk materials
    ( 2017)
    Pfaff, F.
    ;
    Kurz, G.
    ;
    Pieper, C.
    ;
    Maier, Georg
    ;
    Noack, B.
    ;
    Kruggel-Emden, H.
    ;
    Gruna, Robin
    ;
    Hanebeck, U.D.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    Optical belt sorters can be used to sort a large variety of bulk materials. By the use of sophisticated algorithms, the performance of the complex machinery can be further improved. Recently, we have proposed an extension to industrial optical belt sorters that involves tracking the individual particles on the belt using an area scan camera. If the estimated behavior of the particles matches the true behavior, the reliability of the separation process can be improved. The approach relies on multitarget tracking using hard association decisions between the tracks and the measurements. In this paper, we propose to include the orientation in the assessment of the compatibility of a track and a measurement. This allows us to achieve more reliable associations, facilitating a higher accuracy of the tracking results.
  • Publication
    Numerical modelling of the separation of complex shaped particles in an optical belt sorter using a DEM-CFD approach and comparison with experiments
    ( 2017)
    Pieper, C.
    ;
    Maier, Georg
    ;
    Pfaff, F.
    ;
    Kruggel-Emden, H.
    ;
    Gruna, Robin
    ;
    Noack, B.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    ;
    Längle, T.
    ;
    Hanebeck, U.D.
    ;
    Beyerer, Jürgen
    In the growing field of bulk solids handling, automated optical sorting systems are of increasing importance. However, the initial sorter calibration is still very time consuming and the precise optical sorting of many materials still remains challenging. In order to investigate the impact of different operating parameters on the sorting quality, a numerical model of an existing modular optical belt sorter is presented in this study. The sorter and particle interaction is described with the Discrete Element Method (DEM) while the air nozzles required for deflecting undesired material fractions are modelled with Computation Fluid Dynamics (CFD). The correct representation of the resulting particle-fluid interaction is realized through a one-way coupling of the DEM with CFD. Complex shaped particle clusters are employed to model peppercorns also used in experimental investigations. To test the correct implementation of the utilized models, the particle mass flow within the sorter is compared between experiment and simulation. The particle separation results of the developed numerical model of the optical sorting system are compared with matching experimental investigations. The findings show that the numerical model is able to predict the sorting quality of the optical sorting system with reasonable accuracy.
  • Publication
    Numerical investigation of optical sorting using the discrete element method
    ( 2017)
    Pieper, C.
    ;
    Kruggel-Emden, H.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    ;
    Pfaff, F.
    ;
    Noack, B.
    ;
    Hanebeck, U.D.
    ;
    Maier, Georg
    ;
    Gruna, Robin
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    Automated optical sorting systems are important devices in the growing field of bulk solids handling. The initial sorter calibration and the precise optical sorting of many materials is still very time consuming and difficult. A numerical model of an automated optical belt sorter is presented in this study. The sorter and particle interaction is described with the Discrete Element Method (DEM) while the separation phase is considered in a post processing step. Different operating parameters and their influence on sorting quality are investigated. In addition, two models for detecting and predicting the particle movement between the detection point and the separation step are presented and compared, namely a conventional line scan camera model and a new approach combining an area scan camera model with particle tracking.
  • Publication
    Improving material characterization in sensor-based sorting by utilizing motion information
    ( 2017)
    Maier, Georg
    ;
    Pfaff, F.
    ;
    Becker, F.
    ;
    Pieper, C.
    ;
    Gruna, Robin
    ;
    Noack, B.
    ;
    Kruggel-Emden, H.
    ;
    Längle, Thomas
    ;
    Hanebeck, U.D.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    ;
    Beyerer, Jürgen
    Sensor-based sorting provides state-of-the-art solutions for sorting of cohesive, granular materials. Systems are tailored to a task at hand, for instance by means of sensors and implementation of data analysis. Conventional systems utilize scanning sensors which do not allow for extraction of motion related information of objects contained in a material feed. Recently, usage of area-scan cameras to overcome this disadvantage has been proposed. Multitarget tracking can then be used in order to accurately estimate the point in time and position at which any object will reach the separation stage. In this paper, utilizing motion information of objects which can be retrieved from multitarget tracking for the purpose of classification is proposed. Results show that corresponding features can significantly increase classification performance and eventually decrease the detection error of a sorting system.
  • Publication
    Real-time motion prediction using the chromatic offset of line scan cameras
    ( 2017)
    Pfaff, F.
    ;
    Maier, Georg
    ;
    Aristov, M.
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    Noack, B.
    ;
    Gruna, Robin
    ;
    Hanebeck, U.
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    ;
    Pieper, C.
    ;
    Kruggel-Emden, H.
    ;
    Wirtz, S.
    ;
    Scherer, V.
    Auf dem heutigen Stand der Technik der optischen Schüttgutsortierung werden Zeilenkameras mit einfachen Annahmen über die Teilchenbewegung kombiniert, um eine Ausschleusung bestimmter Teilchen zu ermöglichen. Kürzlich haben wir einen experimentellen optischen Bandsortierer mit einer Flächenkamera ausgestattet und gezeigt, dass durch das Verfolgen der Teilchen des Schüttguts die Güte der Vorhersagen und somit auch der Ausschleusung verbessert werden kann. In dieser Arbeit nutzen wir den Farbversatz zwischen den Farbkanälen einer Farbzeilenkamera, um in Echtzeit Informationen über die Bewegung der Teilchen abzuleiten. Dieser Ansatz erlaubt es, die Vorhersagen heutiger optischer Bandsortierer zu verbessern, ohne dass deren Hardware dafür angepasst werden muss.
  • Publication
    Numerical modeling of an automated optical belt sorter using the Discrete Element Method
    ( 2016)
    Pieper, C.
    ;
    Maier, Georg
    ;
    Pfaff, F.
    ;
    Kruggel-Emden, H.
    ;
    Wirtz, S.
    ;
    Gruna, Robin
    ;
    Noack, B.
    ;
    Scherer, V.
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    ;
    Hanebeck, U.
    Optical sorters are important devices in the processing and handling of the globally growing material streams. The precise optical sorting of many bulk solids is still difficult due to the great technical effort necessary for transport and flow control. In this study, particle separation with an automated optical belt sorter is modeled numerically. The Discrete Element Method (DEM) is used to model the sorter and calculate the particle movement as well as particle - particle and particle - wall interactions. The particle ejection stage with air valves is described with the help of a MATLAB script utilizing particle movement information obtained with the DEM. Two models for predicting the particle movement between the detection and separation phase are implemented and compared. In the first model, it is assumed that the particles are moving with belt velocity and without any cross movements and a conventional line scan camera is used for particle detection. In the second model, a more sophisticated approach is employed where the particle motion is predicted with an area scan camera combined with a tracking algorithm. In addition, the influence of different operating parameters like particle shape or conveyor belt length on the separation quality of the system is investigated. Results show that numerical simulations can offer detailed insight into the operation performance of optical sorters and help to optimize operating parameters. The area scan camera approach was found to be superior to the standard line scan camera model in almost all investigated categories.