TY - CHAP A1 - Kreß, Viktor A1 - Zernetsch, Stefan A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Pose Based Trajectory Forecast of Vulnerable Road Users Using Recurrent Neural Networks T2 - ICPR 2021: Pattern Recognition. ICPR International Workshops and Challenges N2 - In this work, we use Recurrent Neural Networks (RNNs) in form of Gated Recurrent Unit (GRU) networks to forecast trajectories of vulnerable road users (VRUs), such as pedestrians and cyclists, in road traffic utilizing the past trajectory and 3D poses as input. The 3D poses represent the postures and movements of limbs and torso and contain early indicators for the transition between motion types, e.g. wait, start, move, and stop. VRUs often only become visible from the perspective of an approaching vehicle shortly before dangerous situations occur. Therefore, a network architecture is required which is able to forecast trajectories after short time periods and is able to improve the forecasts in case of longer observations. This motivates us to use GRU networks, which are able to use time series of varying duration as inputs, and to investigate the effects of different observation periods on the forecasting results. Our approach is able to make reasonable forecasts even for short observation periods. The use of poses improves the forecasting accuracy, especially for short observation periods compared to a solely head trajectory based approach. Different motion types benefit to different extent from the use of poses and longer observation periods. KW - 3D human trajectory forecast KW - Vulnerable road users KW - 3D body pose KW - Fahrerassistenzsystem KW - Fußgänger KW - Radfahrer Y1 - 2020 SN - 978-3-030-68763-2 U6 - https://doi.org/https://doi.org/10.1007/978-3-030-68763-2_5 SP - 57 EP - 71 PB - Springer International Publishing CY - Cham ER - TY - GEN A1 - Doll, Konrad A1 - Köhler, Sebastian A1 - Goldhammer, Michael A1 - Brunsmann, Ulrich T1 - Pedestrian Movement Modelling and Trajectory Prediction at Urban Intersections T2 - International IEEE Conference on Intelligent Transportation Systems (ITSC 2015) N2 - Vortrag KW - Fahrerassistenzsystem KW - Fußgänger Y1 - 2015 CY - Las Palmas de Gran Canaria, Spain ER - TY - CHAP A1 - Hubert, Andreas A1 - Zernetsch, Stefan A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Cyclists starting behavior at intersections T2 - 2017 IEEE Intelligent Vehicles Symposium (IV) KW - Fahrerassistenzsystem KW - Radfahrer Y1 - 2017 U6 - https://doi.org/10.1109/IVS.2017.7995856 SP - 1071 EP - 1077 PB - IEEE CY - Los Angeles, CA, USA ER - TY - JOUR A1 - Kröhn, Michael A1 - Reuter, Norbert A1 - Hahnle, Michael A1 - Prochus, Tobias A1 - Doll, Konrad T1 - Gestengesteuerte Prozessanalyse JF - atp edition - Automatisierungstechnische Praxis KW - Prozessanalyse Y1 - 2016 VL - 58 IS - 12 SP - 26 EP - 33 ER - TY - CHAP A1 - Zernetsch, Stefan A1 - Reichert, Hannes A1 - Kress, Viktor A1 - Doll, Konrad A1 - Sick, Bernhard T1 - A Holistic View on Probabilistic Trajectory Forecasting – Case Study. Cyclist Intention Detection T2 - 2022 IEEE Intelligent Vehicles Symposium (IV) KW - Autonomes Fahrzeug KW - Radfahrer Y1 - 2022 U6 - https://doi.org/https://doi.org/10.1109/IV51971.2022.9827220 SP - 265 EP - 272 PB - IEEE ER - TY - CHAP A1 - Bieshaar, Maarten A1 - Zernetsch, Stefan A1 - Riepe, Katharina A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Cyclist Motion State Forecasting - Going beyond Detection T2 - 2021 IEEE Symposium Series on Computational Intelligence (SSCI) KW - Autonomes Fahrzeug KW - Radfahrer Y1 - 2021 U6 - https://doi.org/10.1109/SSCI50451.2021.9660151 SP - 1 EP - 8 PB - IEEE ER - TY - CHAP A1 - Schneegans, Jan A1 - Eilbrecht, Jan A1 - Zernetsch, Stefan A1 - Bieshaar, Maarten A1 - Doll, Konrad A1 - Stursberg, Olaf A1 - Sick, Bernhard T1 - Probabilistic VRU Trajectory Forecasting for Model-Predictive Planning A Case Study: Overtaking Cyclists T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) KW - Fahrerassistenzsystem KW - Radfahrer KW - Autonomes Fahrzeug Y1 - 2021 U6 - https://doi.org/10.1109/IVWorkshops54471.2021.9669208 SP - 272 EP - 279 PB - IEEE ER - TY - JOUR A1 - Kress, Viktor A1 - Jeske, Fabian A1 - Zernetsch, Stefan A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users’ Trajectories JF - IEEE Transactions on Intelligent Vehicles KW - Fahrerassistenzsystem KW - Autonomes Fahrzeug Y1 - 2023 U6 - https://doi.org/10.1109/TIV.2022.3149624 SN - 2379-8904 VL - 8 IS - 3 SP - 2592 EP - 2603 PB - Institute of Electrical and Electronics Engineers (IEEE) ER - TY - CHAP A1 - Zernetsch, Stefan A1 - Trupp, Oliver A1 - Kress, Viktor A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information T2 - 2021 IEEE International Smart Cities Conference (ISC2) KW - Autonomes Fahrzeug KW - Radfahrer Y1 - 2021 U6 - https://doi.org/10.1109/ISC253183.2021.9562857 SP - 1 EP - 7 PB - IEEE ER - TY - CHAP A1 - Jung, Janis A1 - Hubert, Andreas A1 - Doll, Konrad A1 - Kröhn, Michael A1 - Stadler, Jochen T1 - Prozessinnovation T2 - Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel, Tagungsband, 18. AALE-Konferenz, Pforzheim, 09.03.-11.03.2022 N2 - Manuelle Montageprozesse sind nach wie vor unverzichtbar in vielen Bereichen der produzierenden Industrie. Vor allem die Qualitätskontrolle, sowie das Einlernen neuer Mitarbeitenden stellen Betriebe durch die voranschreitende Digitalisierung vor neue Herausforderungen. Assistenzsysteme können hier helfen, die Lücke zwischen Anforderungen und Qualifikation zu überbrücken. Wir stellen einen Ansatz zur intelligenten Assistenz vor, welcher auf einer kamerabasierten Erkennung von Arbeitsabläufen mit Hilfe von Methoden des maschinellen Lernens beruht. Das Assistenzsystem erzeugt automatisiert Hilfsmaterial zur Unterstützung der Werkenden. Zusätzlich zur Darstellung der technischen Aspekte, werden psychologische Aspekte, wie Akzeptanz und Motivation untersucht. KW - Assistenzsystem KW - Montage KW - Maschinelles Lernen Y1 - 2022 U6 - https://doi.org/10.33968/2022.20 PB - Hochschule für Technik, Wirtschaft und Kultur Leipzig ER - TY - CHAP A1 - Serfling, Benjamin A1 - Reichert, Hannes A1 - Bayerlein, Lorenzo A1 - Doll, Konrad A1 - Radkhah-Lens, Kati T1 - LiDAR Based Semantic Perception for Forklifts in Outdoor Environments T2 - 2025 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) KW - Gabelstapler KW - Autonomes Fahrzeug Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1109/SOLI66289.2025.11396313 SP - 40 EP - 45 PB - IEEE ER - TY - CHAP A1 - Hubert, Andreas A1 - Guo, Chenxi A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Improving Fast 6D Pose Estimation with Adaptive Model Fusion T2 - 2025 5th International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) KW - Maschinelles Lernen KW - Deep Learning KW - Montagezelle Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1109/MLISE66443.2025.11100239 SP - 58 EP - 63 PB - IEEE ER - TY - CHAP A1 - Hubert, Andreas A1 - Guo, C. A1 - Doll, Konrad A1 - Kuhn, F. A1 - Kröhn, M. T1 - Multimodales hochautomatisiert lernendes Assistenzsystem für manuelle Montageprozesse T2 - Automation 2025 KW - Maschinelles Lernen KW - Künstliche Intelligenz KW - Montage Y1 - 2025 SN - 9783181024577 U6 - https://doi.org/https://doi.org/10.51202/9783181024577-575 SP - 575 EP - 590 PB - VDI Verlag ER -