Publikationen
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Ewering, J.-H., Volkmann, B., Ehlers, S. F. G., Seel, T., & Meindl, M. B. (2024). Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline. In 2024 IEEE 63rd Conference on Decision and Control, CDC 2024 (S. 4157-4164). (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC56724.2024.10886241, https://doi.org/10.48550/arXiv.2409.09331
Volkmann, B., Kortmann, K.-P., & Seel, T. (2023). Friction and Road Condition Estimation using Bayesian Networks. In H. Ishii, Y. Ebihara, J. Imura, & M. Yamakita (Hrsg.), 22nd IFAC World Congress (2 Aufl., Band 56, S. 854-861). (IFAC-PapersOnLine; Band 56, Nr. 2). https://doi.org/10.1016/j.ifacol.2023.10.1672
Volkmann, B., & Kortmann, K.-P. (2023). Friction and Road Condition Estimation using Dynamic Bayesian Networks. In 2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI) (International Conference on Multisensor Fusion and Information Integration for Intelligent Systems). IEEE. https://doi.org/10.1109/SDF-MFI59545.2023.10361516
Volkmann, B., Ziaukas, Z., & Jacob, H.-G. (2022). Estimation of Vehicle Attitude and Side-Slip using a Low-Cost IMU and Kinematic Vehicle Constraints. Beitrag in 15th International Symposium on Advanced Vehicle Control - AVEC'22.
Volkmann, B., Kaczor, D., Tantau, M., Schappler, M., & Ortmaier, T. (2020). Sensitivity-based Model Reduction for In-Process Identification of Industrial Robots Inverse Dynamics. In 2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020 (S. 912-919). Artikel 9233709 (IEEE International Conference on Mechatronics and Automation, ICMA 2020). https://doi.org/10.15488/10355, https://doi.org/10.1109/icma49215.2020.9233709