Publikationsliste – Institut für Mechatronische Systeme

Habich, T. L., Mohammad, A., Ehlers, S. F. G., Bensch, M., Seel, T., & Schappler, M. (2026). Generalizable and Fast Surrogates: Model Predictive Control of Articulated Soft Robots using Physics-Informed Neural Networks. IEEE Transactions on Robotics, 42, 619 - 636. https://doi.org/10.1109/TRO.2025.3631818, https://doi.org/10.48550/arXiv.2502.01916

Mohammad, A., Habich, T. L., Seel, T., & Schappler, M. (2026). SafePR: Unified Approach for Safe Parallel Robots by Contact Detection and Reaction with Redundancy Resolution. IEEE transactions on robotics, 42, 1784-1803. https://doi.org/10.1109/TRO.2026.3666147

Pawluchin, A., Habich, T.-L., Seel, T., & Boblan, I. (2026). Data-driven pressure controller using proportional piezoelectric valves for soft pneumatic actuators. MECHATRONICS, 113, 103428. Artikel 103428. https://doi.org/10.1016/j.mechatronics.2025.103428

Sterneck, T., Zumsande, J., Habich, T. L., Mohammad, A., Ehlers, S., Schappler, M., & Seel, T. (2025). A Modular and Open-Source Remote Laboratory for Practical Education on Mechatronic Test Benches. in R. Balogh, D. Obdržálek, & N. Fachantidis (Hrsg.), Robotics in Education - Proceedings of the RiE 2025 Conference (S. 460-473). (Lecture Notes in Networks and Systems; Band 1544 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-98762-5_39

Bensch, M., Job, T. D., Habich, T. L., Seel, T., & Schappler, M. (2024). Physics-Informed Neural Networks for Continuum Robots: Towards Fast Approximation of Static Cosserat Rod Theory. in 2024 IEEE International Conference on Robotics and Automation, ICRA 2024 (S. 17293-17299). (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA57147.2024.10610742

Habich, T.-L., Schappler, M., & Ortmaier, T. (2024). Grundlagen der Robotik. in U. Grünhaupt, & M. Ruskowski (Hrsg.), Handbuch der Mess- und Automatisierungstechnik in der Produktion (S. 1-14). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-62424-1_59-3

Habich, T. L., Haack, J., Belhadj, M., Lehmann, D., Seel, T., & Schappler, M. (2024). SPONGE: Open-Source Designs of Modular Articulated Soft Robots. IEEE Robotics and Automation Letters, 9(6), 5346-5353. https://doi.org/10.48550/arXiv.2404.10734, https://doi.org/10.1109/LRA.2024.3388855

Krauss, H., Habich, T.-L., Bartholdt, M., Seel, T., & Schappler, M. (2024). Domain-Decoupled Physics-informed Neural Networks with Closed-Form Gradients for Fast Model Learning of Dynamical Systems. in Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics (Band 1, S. 55-66). (Proceedings of the International Conference on Informatics in Control, Automation and Robotics). https://doi.org/10.5220/0012935200003822, https://doi.org/10.48550/arXiv.2408.14951

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

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

Habich, T. L., Hueter, M., Schappler, M., & Spindeldreier, S. (2023). Intuitive Telemanipulation of Hyper-Redundant Snake Robots within Locomotion and Reorientation using Task-Priority Inverse Kinematics. in Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation (S. 9651-9657). (Proceedings - IEEE International Conference on Robotics and Automation; Band 2023-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.48550/arXiv.2303.00065, https://doi.org/10.1109/ICRA48891.2023.10161124

Habich, T. L., Kleinjohann, S., & Schappler, M. (2023). Learning-based Position and Stiffness Feedforward Control of Antagonistic Soft Pneumatic Actuators using Gaussian Processes. in 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023 (IEEE International Conference on Soft Robotics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.48550/arXiv.2303.01840, https://doi.org/10.1109/RoboSoft55895.2023.10122057

Mohammad, A., Schappler, M., Habich, T.-L., & Ortmaier, T. (2023). Safe Collision and Clamping Reaction for Parallel Robots During Human-Robot Collaboration. in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (S. 5966-5973). (Key-title Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems). IEEE. https://doi.org/10.48550/arXiv.2308.09656, https://doi.org/10.1109/iros55552.2023.10341581

Habich, T.-L., Stuede, M., Labbé, M., & Spindeldreier, S. (2021). Have I been here before? Learning to Close the Loop with LiDAR Data in Graph-Based SLAM. in Proceedings of the 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM): July 12-16, 2021, Delft, The Netherlands (S. 504-510) https://doi.org/10.1109/AIM46487.2021.9517565

Habich, T.-L., Kaczor, D., Tappe, S., & Ortmaier, T. (2019). Online Learning of the Inverse Dynamics with Parallel Drifting Gaussian Processes: Implementation of an Approach for Feedforward Control of a Parallel Kinematic Industrial Robot. in Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019 (S. 962-969). Artikel 8816298 (Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMA.2019.8816298

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