TY - CHAP A1 - Engemann, Heiko A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Ning, Chuanfang A1 - Anwar, Saqib T1 - AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation T2 - Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020 N2 - We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level. Y1 - 2020 SN - 978-1-64368-137-5 U6 - https://doi.org/10.3233/FAIA200770 N1 - Frontiers in Artificial Intelligence and Applications. Vol 332 SP - 89 EP - 97 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Engemann, Heiko A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Cönen, Patrick A1 - Dawar, Harshal T1 - OMNIVIL - an autonomous mobile manipulator for flexible production JF - Sensors Y1 - 2020 SN - 1424-8220 U6 - https://doi.org/10.3390/s20247249 N1 - Special issue: Sensor Networks Applications in Robotics and Mobile Systems VL - 20 IS - 24, art. no. 7249 SP - 1 EP - 30 PB - MDPI CY - Basel ER - TY - CHAP A1 - Hoegen, Anne von A1 - Doncker, Rik W. De A1 - Rütters, René T1 - Teaching Digital Control of Operational Amplifier Processes with a LabVIEW Interface and Embedded Hardware T2 - 2020 23rd International Conference on Electrical Machines and Systems (ICEMS) N2 - Control engineering theory is hard to grasp for undergraduates during the first semesters, as it deals with the dynamical behavior of systems also in combination with control strategies on an abstract level. Therefore, operational amplifier (OpAmp) processes are reasonable and very effective systems to connect mathematical description with actual system’s behavior. In this paper, we present an experiment for a laboratory session in which an embedded system, driven by a LabVIEW human machine interface (HMI) via USB, controls the analog circuits.With this setup we want to show the possibility of firstly, analyzing a first order process and secondly, designing a P-and PI-controller. Thereby, the theory of control engineering is always applied to the empirical results in order to break down the abstract level for the students. Y1 - 2020 U6 - https://doi.org/10.23919/ICEMS50442.2020.9290928 N1 - 23rd International Conference on Electrical Machines and Systems (ICEMS), 24-27 November 2020, Hamamatsu, Japan SP - 1117 EP - 1122 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Gamified Virtual Reality Training Environment for the Manufacturing Industry T2 - Proceedings of the 2020 19th International Conference on Mechatronics – Mechatronika (ME) N2 - Industry 4.0 imposes many challenges for manufacturing companies and their employees. Innovative and effective training strategies are required to cope with fast-changing production environments and new manufacturing technologies. Virtual Reality (VR) offers new ways of on-the-job, on-demand, and off-premise training. A novel concept and evaluation system combining Gamification and VR practice for flexible assembly tasks is proposed in this paper and compared to existing works. It is based on directed acyclic graphs and a leveling system. The concept enables a learning speed which is adjustable to the users’ pace and dynamics, while the evaluation system facilitates adaptive work sequences and allows employee-specific task fulfillment. The concept was implemented and analyzed in the Industry 4.0 model factory at FH Aachen for mechanical assembly jobs. Y1 - 2020 U6 - https://doi.org/10.1109/ME49197.2020.9286661 N1 - 2020 19th International Conference on Mechatronics – Mechatronika (ME), Prague, Czech Republic, December 2–4, 2020 SP - 1 EP - 6 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Morat, Mareike A1 - Faude, Oliver A1 - Hanssen, Henner A1 - Ludyga, Sebastian A1 - Zacher, Jonas A1 - Eibl, Angi A1 - Albracht, Kirsten A1 - Donath, Lars T1 - Agility Training to Integratively Promote Neuromuscular, Cognitive, Cardiovascular and Psychosocial Function in Healthy Older Adults: A Study Protocol of a One-Year Randomized-Controlled Trial JF - International Journal of Environmental Research and Public Health N2 - Exercise training effectively mitigates aging-induced health and fitness impairments. Traditional training recommendations for the elderly focus separately on relevant physiological fitness domains, such as balance, flexibility, strength and endurance. Thus, a more holistic and functional training framework is needed. The proposed agility training concept integratively tackles spatial orientation, stop and go, balance and strength. The presented protocol aims at introducing a two-armed, one-year randomized controlled trial, evaluating the effects of this concept on neuromuscular, cardiovascular, cognitive and psychosocial health outcomes in healthy older adults. Eighty-five participants were enrolled in this ongoing trial. Seventy-nine participants completed baseline testing and were block-randomized to the agility training group or the inactive control group. All participants undergo pre- and post-testing with interim assessment after six months. The intervention group currently receives supervised, group-based agility training twice a week over one year, with progressively demanding perceptual, cognitive and physical exercises. Knee extension strength, reactive balance, dual task gait speed and the Agility Challenge for the Elderly (ACE) serve as primary endpoints and neuromuscular, cognitive, cardiovascular, and psychosocial meassures serve as surrogate secondary outcomes. Our protocol promotes a comprehensive exercise training concept for older adults, that might facilitate stakeholders in health and exercise to stimulate relevant health outcomes without relying on excessively time-consuming physical activity recommendations. KW - agility KW - prevention KW - healthy aging KW - community dwelling KW - psychosocial Y1 - 2020 U6 - https://doi.org/10.3390/ijerph17061853 SN - 1660-4601 VL - 17 IS - 6 SP - 1 EP - 14 PB - MDPI CY - Basel ER - TY - JOUR A1 - Ketelhut, Maike A1 - Brügge, G. M. A1 - Göll, Fabian A1 - Braunstein, Bjoern A1 - Albracht, Kirsten A1 - Abel, Dirk T1 - Adaptive iterative learning control of an industrial robot during neuromuscular training JF - IFAC PapersOnLine N2 - To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur. KW - Iterative learning control KW - Robotic rehabilitation KW - Adaptive control Y1 - 2020 U6 - https://doi.org/10.1016/j.ifacol.2020.12.741 SN - 2405-8963 VL - 53 IS - 2 SP - 16468 EP - 16475 PB - Elsevier CY - Amsterdam ER - TY - GEN T1 - Ordnung zur Aufhebung der Prüfungsordnung für die Masterstudiengänge „Energiewirtschaft & Informatik“ (3 Semester) und „Energiewirtschaft & Informatik“ (4 Semester) vom 4. Mai 2016 (FH-Mitteilung Nr. 59/2016) Fachbereich Energietechnik Fachbereich Medizintechnik und Technomathematik an der Fachhochschule Aachen : vom 16. Januar 2020 T3 - FH-Mitteilungen - 1/2020 KW - Amtliche Mitteilung KW - Aufhebungsordnung KW - Prüfungsordnung KW - Master KW - Energiewirtschaft & Informatik Y1 - 2020 ER - TY - GEN T1 - Verwaltungs- und Benutzungsordnung des Solar-Instituts Jülich (SIJ) : vom 27. Januar 2020 T3 - FH-Mitteilungen - 2/2020 KW - Amtliche Mitteilung KW - Verwaltungs- und Benutzungsordnung KW - Solar-Institut Jülich KW - SIJ Y1 - 2020 ER - TY - GEN T1 - Verwaltungs- und Benutzungsordnung des Solar-Instituts Jülich (SIJ) vom 27. Januar 2020 : berichtigt durch Bekanntmachung vom 18. März 2020 (FH-Mitteilung Nr. 27/2020) T3 - FH-Mitteilungen - 2b/2020 KW - Amtliche Mitteilung KW - Verwaltungs- und Benutzungsordnung KW - Solar-Institut Jülich KW - SIJ KW - berichtigt Y1 - 2020 ER - TY - GEN A1 - Schulze-Buxloh, Lina A1 - Groß, Rolf Fritz A1 - Cheng, Kevin Toni T1 - Development and manufacturing of an interactive three-dimensional phase diagram of carbon dioxide for teaching sessions in thermodynamics T2 - Proceedings of the International Conference The Future of Education 2020 Y1 - 2020 ER -