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 - Müller, Tim M. A1 - Schmitt, Andreas A1 - Leise, Philipp A1 - Meck, Tobias A1 - Altherr, Lena A1 - Pelz, Peter F. A1 - Pfetsch, Marc E. T1 - Validation of an optimized resilient water supply system T2 - Uncertainty in Mechanical Engineering N2 - Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems. KW - Optimization KW - Mixed-integer nonlinear programming KW - Water distribution system KW - Resilience KW - Validation Y1 - 2021 SN - 978-3-030-77255-0 SN - 978-3-030-77256-7 U6 - http://dx.doi.org/10.1007/978-3-030-77256-7_7 N1 - Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), June 7–8, 2021 SP - 70 EP - 80 PB - Springer CY - Cham ER - TY - CHAP A1 - Hüning, Felix T1 - Sustainable changes beyond covid-19 for a second semester physics course for electrical engineering students T2 - Blended Learning in Engineering Education: challenging, enlightening – and lasting? N2 - The course Physics for Electrical Engineering is part of the curriculum of the bachelor program Electrical Engineering at University of Applied Science Aachen. Before covid-19 the course was conducted in a rather traditional way with all parts (lecture, exercise and lab) face-to-face. This teaching approach changed fundamentally within a week when the covid-19 limitations forced all courses to distance learning. All parts of the course were transformed to pure distance learning including synchronous and asynchronous parts for the lecture, live online-sessions for the exercises and self-paced labs at home. Using these methods, the course was able to impart the required knowledge and competencies. Taking the teacher’s observations of the student’s learning behaviour and engagement, the formal and informal feedback of the students and the results of the exams into account, the new methods are evaluated with respect to effectiveness, sustainability and suitability for competence transfer. Based on this analysis strong and weak points of the concept and countermeasures to solve the weak points were identified. The analysis further leads to a sustainable teaching approach combining synchronous and asynchronous parts with self-paced learning times that can be used in a very flexible manner for different learning scenarios, pure online, hybrid (mixture of online and presence times) and pure presence teaching. Y1 - 2021 SN - 978-2-87352-023-6 N1 - SEFI 49th Annual Conference Technische Universität Berlin (online), 13 – 16 September 2021 SP - 1405 EP - 1409 ER - TY - CHAP A1 - Hüning, Felix A1 - Wache, Franz-Josef A1 - Magiera, David T1 - Redundant bus systems using dual-mode radio T2 - Proceedings of Sixth International Congress on Information and Communication Technology N2 - Communication via serial bus systems, like CAN, plays an important role for all kinds of embedded electronic and mechatronic systems. To cope up with the requirements for functional safety of safety-critical applications, there is a need to enhance the safety features of the communication systems. One measure to achieve a more robust communication is to add redundant data transmission path to the applications. In general, the communication of real-time embedded systems like automotive applications is tethered, and the redundant data transmission lines are also tethered, increasing the size of the wiring harness and the weight of the system. A radio link is preferred as a redundant transmission line as it uses a complementary transmission medium compared to the wired solution and in addition reduces wiring harness size and weight. Standard wireless links like Wi-Fi or Bluetooth cannot meet the requirements for real-time capability with regard to bus communication. Using the new dual-mode radio enables a redundant transmission line meeting all requirements with regard to real-time capability, robustness and transparency for the data bus. In addition, it provides a complementary transmission medium with regard to commonly used tethered links. A CAN bus system is used to demonstrate the redundant data transfer via tethered and wireless CAN. Y1 - 2021 SN - 978-981-16-2379-0 SN - 978-981-16-2380-6 U6 - http://dx.doi.org/10.1007/978-981-16-2380-6_73 N1 - Proceedings of Sixth International Congress on Information and Communication Technology, ICICT 2021, Brunel University, London, February 25–26, 2021 SP - 835 EP - 842 PB - Springer CY - Singapore ER - TY - CHAP A1 - Hoegen, Anne von A1 - Doncker, Rik W. De A1 - Bragard, Michael A1 - Hoegen, Svenja von T1 - Problem-Based Learning in Automation Engineering: Performing a Remote Laboratory Session Serving Various Educational Attainments T2 - 2021 IEEE Global Engineering Education Conference (EDUCON) Y1 - 2021 U6 - http://dx.doi.org/10.1109/EDUCON46332.2021.9453925 SP - 1605 EP - 1614 ER - TY - CHAP A1 - Hüning, Felix A1 - Stüttgen, Marcel T1 - Work in Progress: Interdisciplinary projects in times of COVID-19 crisis – challenges, risks and chances T2 - 2021 IEEE Global Engineering Education Conference (EDUCON) Y1 - 2021 U6 - http://dx.doi.org/10.1109/EDUCON46332.2021.9454006 SP - 1175 EP - 1179 ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - http://dx.doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Ritschel, Konstantin A1 - Stenzel, Adina A1 - Czarnecki, Christian A1 - Hong, Chin-Gi ED - Gesellschaft für Informatik e.V. (GI), T1 - Realizing robotic process automation potentials: an architectural perspective on a real-life implementation case T2 - GI Edition Proceedings Band 314 "INFORMATIK 2021" Computer Science & Sustainability N2 - The initial idea of Robotic Process Automation (RPA) is the automation of business processes through a simple emulation of user input and output by software robots. Hence, it can be assumed that no changes of the used software systems and existing Enterprise Architecture (EA) is required. In this short, practical paper we discuss this assumption based on a real-life implementation project. We show that a successful RPA implementation might require architectural work during analysis, implementation, and migration. As practical paper we focus on exemplary lessons-learned and new questions related to RPA and EA. KW - Robotic Process Automation KW - Enterprise Architecture KW - Implementation Case Y1 - 2021 SN - 9783885797081 SN - 1617-5468 N1 - INFORMATIK 2021 – 51. Jahrestagung der Gesellschaft für Informatik, 27. September – 01. Oktober 2021 / Virtuell, Berlin. https://informatik2021.gi.de/ SP - 1303 EP - 1311 PB - Köllen CY - Bonn ER - TY - CHAP A1 - Ferrein, Alexander A1 - Meeßen, Marcus A1 - Limpert, Nicolas A1 - Schiffer, Stefan ED - Lepuschitz, Wilfried T1 - Compiling ROS Schooling Curricula via Contentual Taxonomies T2 - Robotics in Education Y1 - 2021 SN - 978-3-030-67411-3 U6 - http://dx.doi.org/10.1007/978-3-030-67411-3_5 N1 - RiE: International Conference on Robotics in Education (RiE); Advances in Intelligent Systems and Computing book series (AISC, volume 1316) SP - 49 EP - 60 PB - Springer CY - Cham ER - TY - CHAP A1 - Heuermann, Holger A1 - Harzheim, Thomas A1 - Mühmel, Marc T1 - A maritime harmonic radar search and rescue system using passive and active tags T2 - 2020 17th European Radar Conference (EuRAD) KW - Harmonic Radar KW - Rescue System KW - Frequency Doubler KW - Transponder KW - Tag Y1 - 2021 SN - 978-2-87487-061-3 U6 - http://dx.doi.org/10.1109/EuRAD48048.2021.00030 N1 - Proceedings of the 17th European Radar Conference, 13th - 15th January 2021, Utrecht, Netherlands SP - 73 EP - 76 PB - IEEE ER -