TY - CHAP A1 - Eltester, Niklas Sebastian A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - A smart factory setup based on the RoboCup logistics league T2 - 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS) N2 - In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs. Y1 - 2020 U6 - http://dx.doi.org/10.1109/ICPS48405.2020.9274766 N1 - 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS), 10-12 June 2020, Tampere, Finland. SP - 297 EP - 302 PB - IEEE ER - TY - CHAP A1 - Cordes, Sven A1 - Gligorevic, Snjezana A1 - Blicharski, Peter T1 - Analysis of sine precision influence on DOA estimation using the MUSIC algorithm T2 - 2019 20th International Radar Symposium (IRS) Y1 - 2019 SN - 978-3-7369-9860-5 U6 - http://dx.doi.org/10.23919/IRS.2019.8768162 SP - 1 EP - 10 ER - TY - CHAP A1 - Donner, Ralf A1 - Rabel, Matthias A1 - Scholl, Ingrid A1 - Ferrein, Alexander A1 - Donner, Marc A1 - Geier, Andreas A1 - John, André A1 - Köhler, Christian A1 - Varga, Sebastian T1 - Die Extraktion bergbaulich relevanter Merkmale aus 3D-Punktwolken eines untertagetauglichen mobilen Multisensorsystems T2 - Tagungsband Geomonitoring Y1 - 2019 U6 - http://dx.doi.org/10.15488/4515 SP - 91 EP - 110 ER - TY - CHAP A1 - Steinbauer, Gerald A1 - Ferrein, Alexander T1 - CogRob 2018 : Cognitive Robotics Workshop. Proceedings of the 11th Cognitive Robotics Workshop 2018 co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018). Tempe, AZ, USA, October 27th, 2018. T2 - CEUR workshop proceedings Y1 - 2019 SN - 1613-0073 N1 - edited by Gerald Steinbauer, Alexander Ferrein IS - Vol-2325 ER - TY - CHAP A1 - Schiffer, Fabian A1 - Bragard, Michael T1 - Cascaded LQ and Field-Oriented Control of a Mobile Inverse Pendulum (Segway) with Permanent Magnet Synchronous Machines T2 - 2019 20th International Conference on Research and Education in Mechatronics (REM) Y1 - 2019 SN - 978-1-5386-9257-8 U6 - http://dx.doi.org/10.1109/REM.2019.8744101 SP - 1 EP - 8 ER - TY - CHAP A1 - Bragard, Michael A1 - Sube, Maike A1 - Schneider, Maike A1 - Jungemann, Christoph T1 - Introducing a Cross-University Bachelor’s Programme with Orientation Semester - Enabling a Permeable Academic Education System T2 - 2019 20th International Conference on Research and Education in Mechatronics (REM) Y1 - 2019 SN - 978-1-5386-9257-8 U6 - http://dx.doi.org/10.1109/REM.2019.8744132 SP - 1 EP - 6 ER - TY - CHAP A1 - Weber, Niklas A1 - Wolf, Martin ED - Barton, Thomas T1 - Datenerhebung für die CDG-Forschung T2 - Prozesse, Technologie, Anwendungen, Systeme und Management 2017 : angewandte Forschung in der Wirtschaftsinformatik : Tagungsband zur 30. AKWI-Jahrestagung vom 17.09.2017 bis 20.09.2017 an der Hochschule Aschaffenburg / Arbeitskreis Wirtschaftsinformatik an Fachhochschulen (AKWI) Y1 - 2017 SN - 978-3-944330-56-3 SP - 218 EP - 227 PB - mana-Buch CY - Heide ER - TY - CHAP A1 - Chajan, Eduard A1 - Schulte-Tigges, Joschua A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Matheis, Dominik A1 - Walter, Thomas T1 - GPU based model-predictive path control for self-driving vehicles T2 - IEEE Intelligent Vehicles Symposium (IV) N2 - One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments. KW - Heuristic algorithms KW - Computational modeling KW - model-predictive control KW - GPU KW - autonomous driving Y1 - 2021 SN - 978-1-7281-5394-0 U6 - http://dx.doi.org/10.1109/IV48863.2021.9575619 N1 - 2021 IEEE Intelligent Vehicles Symposium (IV) July 11-17, 2021. Nagoya, Japan SP - 1243 EP - 1248 PB - IEEE ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. ED - Neufeld, Janis S. ED - Buscher, Udo ED - Lasch, Rainer ED - Möst, Dominik ED - Schönberger, Jörn T1 - Assessing and Optimizing the Resilience of Water Distribution Systems Using Graph-Theoretical Metrics T2 - Operations Research Proceedings 2019 N2 - Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience. KW - OR 2019 KW - business analytics KW - decision analytics KW - digital economy KW - mathematical optimization Y1 - 2020 SN - 978-3-030-48439-2 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_63 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 521 EP - 527 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Simon, Nicolai A1 - Altherr, Lena T1 - Comparison of Piecewise Linearization Techniques to Model Electric Motor Efficiency Maps: A Computational Study T2 - Operations Research Proceedings 2019 N2 - To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables. KW - MINLP KW - Powertrain KW - Piecewise linearization KW - Efficiency optimization Y1 - 2020 SN - 978-3-030-48439-2 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_55 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 457 EP - 463 PB - Springer CY - Cham ER -