Dustin Lehmann
Photo: SCIoI
Dustin Lehmann is an aerospace engineer with a specialization in control theory and an interest in applying control-theoretic concepts to learning and multi-agent systems.
He joined SCIoI as a doctoral researcher in October 2019.
Dustin graduated in Aerospace Engineering at TU Berlin, focusing on control theory. In his SCIoI doctoral project, he worked on applying control theory concepts to multi-agent learning problems. In particular, he focused on using learning-control approaches as well as distributed and network-control concepts.
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Lehmann, D., Drebinger, P., Seel, T., & Raisch, J. (2023). Data-Driven Dynamic Input Transfer for Learning Control in Multi-Agent Systems with Heterogeneous Unknown Dynamics. 2023 62nd IEEE Conference on Decision and Control (CDC), 2358–2365. https://doi.org/10.1109/CDC49753.2023.10383433
Meindl, M., Lehmann, D., & Seel, T. (2022). Bridging Reinforcement Learning and Iterative Learning Control: Autonomous Motion Learning for Unknown, Nonlinear Dynamics. Frontiers in Robotics and AI, 9, 793512. https://doi.org/10.3389/frobt.2022.793512
Meindl, M., Molinari, F., Lehmann, D., & Seel, T. (2022). Collective Iterative Learning Control: Exploiting Diversity in Multi-Agent Systems for Reference Tracking Tasks. IEEE Transactions on Control Systems Technology, 30(4), 1390–1402. https://doi.org/10.1109/TCST.2021.3109646
