2024
Meindl, M., Mönkemöller, R., & Seel, T. (2024). Autonomous Iterative Motion Learning (AI-MOLE) of a SCARA Robot for Automated Myocardial Injection. IFAC-PapersOnLine, 58(24), 380-385. https://doi.org/10.48550/arXiv.2409.06361, https://doi.org/10.1016/j.ifacol.2024.11.067
Meindl, M., Bachhuber, S., & Seel, T. (2024). Reference-Adapting Iterative Learning Control for Motion Optimization in Constrained Environments. in 2024 IEEE 63rd Conference on Decision and Control, CDC 2024 (S. 4143-4150). (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC56724.2024.10886730
Meindl, M., Campe, F., Lehmann, D., & Seel, T. (2024). Solving Motion Tasks with Challenging Dynamics by Combining Kinodynamic Motion Planning and Iterative Learning Control. in 2024 European Control Conference, ECC 2024 (S. 1208-1213). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ECC64448.2024.10590944
Moenkemoeller, R., Budde, L., Martin, U., Martens, A., & Seel, T. (2024). Towards Less Invasive Instruments For Cardiac Tissue Stabilizing. Current Directions in Biomedical Engineering, 10(4), 445–448. https://doi.org/10.1515/cdbme-2024-2109
Mohammad, A., Muscheid, H., Schappler, M., & Seel, T. (2024). Quantifying Uncertainties of Contact Classifications in a Human-Robot Collaboration with Parallel Robots. in C. Piazza, P. Capsi-Morales, L. Figueredo, M. Keppler, & H. Schütze (Hrsg.), Human-Friendly Robotics 2023: HFR: 16th International Workshop on Human-Friendly Robotics (1. Aufl., S. 137-150). (Springer Proceedings in Advanced Robotics (SPAR); Nr. 29). Springer. https://doi.org/10.1007/978-3-031-55000-3_10
Pawluchin, A., Meindl, M., Weygers, I., Seel, T., & Boblan, I. (2024). Gaussian process-based nonlinearity compensation for pneumatic soft actuators. At-Automatisierungstechnik, 72(5), 440-448. https://doi.org/10.1515/auto-2023-0237
Rostalski, P., Schanze, T., & Seel, T. (2024). Special issue AUTOMED. At-Automatisierungstechnik, 72(5), 387-388. https://doi.org/10.1515/auto-2024-0057
Schäfke, H., Habich, T.-L., Muhmann, C., Ehlers, S., Seel, T., & Schappler, M. (2024). Learning-Based Nonlinear Model Predictive Control of Articulated Soft Robots Using Recurrent Neural Networks. IEEE Robotics and Automation Letters, 9(12), 11609-11616. Artikel 11609. https://doi.org/10.1109/LRA.2024.3495579
Schappler, M., & Ortmaier, T. (2024). Roboteranwendungen. in U. Grünhaupt, & M. Ruskowski (Hrsg.), Handbuch der Mess- und Automatisierungstechnik in der Produktion Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-62424-1_61-1
Seel, T., Kolditz, T., Overmeyer, L., Lukas, M., Leineweber, S., Leineweber, A., Orimi, A. G., & Kuhlgatz, T. (2024). KI im Maschinenbau: Zu den Auswirkungen und Veränderungen in Wissenschaft und Arbeitswelt. Uni-Magazin, Hannover, 1(2), 12-16. https://doi.org/10.15488/17789
Stüde, M. (2024). Environment and task modeling of long-term-autonomous service robots. [Dissertation, Gottfried Wilhelm Leibniz Universität Hannover]. Leibniz Universität Hannover. https://doi.org/10.15488/16370
Tantau, M. (2024). Strukturidentifikation und Unterscheidbarkeit von Modellen für elektromechanische Antriebsstränge: Structure identification and distinguishability for models of electromechanical drive trains. [Dissertation, Gottfried Wilhelm Leibniz Universität Hannover]. Leibniz Universität Hannover. https://doi.org/10.15488/17543
Weber, D. O. M., Gühmann, C., & Seel, T. (2024). FranSys—A Fast Non-Autoregressive Recurrent Neural Network for Multi-Step Ahead Prediction. IEEE ACCESS, 12, 145130 - 145147. https://doi.org/10.1109/ACCESS.2024.3473014
Weiss, M., Stirling, A., Pawluchin, A., Lehmann, D., Hannemann, Y., Seel, T., & Boblan, I. (2024). Achieving Velocity Tracking Despite Model Uncertainty for a Quadruped Robot with a PD-ILC Controller. in 2024 European Control Conference, ECC 2024 (S. 134-140). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ECC64448.2024.10590932
Weiss, M., Pawluchin, A., Seel, T., & Boblan, I. (2024). Learning of a Rapid Prototyping Gait Library for a Quadruped Robot Using PD-ILC and Gaussian Processes. in 2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV) (S. 1213-1218). (International Conference on Control, Automation, Robotics, and Vision). IEEE. https://doi.org/10.1109/ICARCV63323.2024.10821620
Zeipel, H., Seel, T., Habich, T.-L., & Ehlers, S. F. G. (2024). Fast and Accurate Prediction of Vehicle Dynamics using Physics-Informed Neural Networks. Vorzeitige Online-Publikation. https://doi.org/10.36227/techrxiv.173398186.65085317/v1
2023
Ahrens, M. (2023). Aktive, modellbasierte Verschleißbeeinflussung beim Außenrundeinstechschleifen mittels elektromagnetischer Aktoren. [Dissertation, Gottfried Wilhelm Leibniz Universität Hannover]. https://doi.org/10.15488/13260
Bachhuber, S., Lehmann, D., Dorschky, E., Koelewijn, A. D., Seel, T., & Weygers, I. (2023). Plug-and-Play Sparse Inertial Motion Tracking With Sim-to-Real Transfer. IEEE Sensors Letters, 7(10), Artikel 7004904. https://doi.org/10.1109/LSENS.2023.3307122
Badilla-Solórzano, J., Ihler, S., Gellrich, N. C., & Spalthoff, S. (2023). Improving instrument detection for a robotic scrub nurse using multi-view voting. International journal of computer assisted radiology and surgery, 18(11), 1961-1968. https://doi.org/10.1007/s11548-023-03002-0
Bartholdt, M., Berthold, R., & Schappler, M. (2023). Towards a Modular Framework for Visco-Hyperelastic Simulations of Soft Material Manipulators with Well-Parameterised Material. in 2023 IEEE International Conference on Soft Robotics (RoboSoft) (IEEE International Conference on Soft Robotics). IEEE. https://doi.org/10.15488/15183, https://doi.org/10.1109/robosoft55895.2023.10122047