M.Sc. Ricus Husmann

Wissenschaftlicher Mitarbeiter

Kontakt

Universität Rostock
Lehrstuhl für Mechatronik

Justus-von-Liebig Weg 6
18059 Rostock
Raum: 03

Tel.: +49 381 / 498 - 9216
Fax: +49 381 / 498 - 9092
E-Mail:Ricus.Husmann(at)uni-rostock.de

Sprechstunde

Nach vorheriger Terminvereinbarung per Telefon oder E-Mail

Forschung

  • Datenbasierte Modellbildungsmethoden
  • Regelungsorientierte Modellbildung thermofluidischer Systeme
  • Kombination von datenbasierten und modellgestützten Regelungsansätzen

Lehre

Sommersemester:
Übung und Praktikum zur LV Optimierungsmethoden in der Mechatronik

Übung und Praktikum zur LV Aktive Systeme in Kraftfahrzeugen

 

Wintersemester:
Übung und Praktikum zur LV Regelungssysteme im Zustandsraum

Begutachtete Kongressbeiträge

  1. Ole Uphaus, Ricus Husmann, Sven Weishaupt and Harald Aschemann: AI-MOLEs: Improving Autonomous Iterative Motion Learning (AI-MOLE) With Stochastic Uncertainty Information. 30th International Conference on System Theory, Control and Computing (ICSTCC). Iasi, Romania, 2026 (accepted).
  2. Sven Weishaupt, Ricus Husmann and Harald Aschemann: Smoothing B-Splines via Quadratic Programming for Reinforcement Learning-Based Path Planning. 30th International Conference on System Theory, Control and Computing (ICSTCC). Iasi, Romania, 2026 (accepted).
  3. Ricus Husmann, Sven Weishaupt, Malin Lotta Husmann and Harald Aschemann: Online Learning-Based Control with Guaranteed Error Bounds for a Class of Nonlinear Systems. 23rd IFAC World Congress. Busan, Republic of Korea, 2026.
  4. Sven Weishaupt, Ricus Husmann and Harald Aschemann: Smooth Reinforcement Learning-Based Path Planning for a 7-DoF Robot Manipulator With Regularized Weighted B-Splines. 23rd IFAC World Congress. Busan, Republic of Korea, 2026.
  5. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Extending Gaussian Process Submodel Online Learning (GPSOL) to State-Dependent and Time-Varying Hidden Functions. 23rd IFAC World Congress. Busan, Republic of Korea, 2026.
  6. Sven Weishaupt, Ricus Husmann and Harald Aschemann: Physics-Informed LSTM Networks for an Improved Tracking Control of a Pneumatic Rodless Cylinder. AIM2026 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Genova, Italy, 2026.
  7. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Recursive Gaussian Process Regression with Integrated Monotonicity Assumptions for Control Applications. 22nd International Conference on Informatics in Control (ICINCO 2025). Marbella, Spain, 2025.
  8. Sven Weishaupt, Ricus Husmann and Harald Aschemann: Improving Generalization and Training Speed of Deep Reinforcement Learning-Based Robotic Path Planning With Vectorized Environments. The 51st Annual Conference of the IEEE Industrial Electronics Society (IECON 2025). Madrid, Spain, 2025.
  9. Sven Weishaupt, Ricus Husmann, Kaneewar Ibrahim and Harald Aschemann: Deep Reinforcement Learning-Based Collision-Free Path Planning for Robotic Manipulators With Dynamic State Vector Sorting. The 51st Annual Conference of the IEEE Industrial Electronics Society (IECON 2025). Madrid, Spain, 2025.
  10. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Direct Integration of Recursive Gaussian Process Regression Into Extended Kalman Filters With Application to Vapor Compression Cycle Control. 13th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2025). Reykjavík, Iceland, 2025.
  11. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Combination of Kalman Filtering and Recursive Gaussian Process Regression With Application to Vapor Compression Cycle Control. 23rd European Control Conference (ECC). Thessaloniki, Greece, 2025.
  12. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Nonlinear Control of a Vapor Compression Cycle Based on a Partial IOL. 50th Annual Conference of the IEEE Industrial Electronics Society (IECON 2024). Chicago, USA, 2024.
  13. Ricus Husmann and Harald Aschemann: Tracking Control for Thermofluidic Systems With Input Constraints and Relative Degree One. 50th Annual Conference of the IEEE Industrial Electronics Society (IECON 2024). Chicago, USA, 2024.
  14. Sven Weishaupt, Ricus Husmann and Harald Aschemann: Boosting Deep Reinforcement Learning-Based Path Planning for Robotic Manipulators With Egocentric State Space Descriptions. 50th Annual Conference of the IEEE Industrial Electronics Society (IECON 2024). Chicago, USA, 2024.
  15. Sven Weishaupt, Harald Aschemann: Exploiting Physics to Learn an Optimal Swing-Up-Strategy for a Variable-Length Pendulum Using Deep Reinforcement Learning. 50th Annual Conference of the IEEE Industrial Electronics Society (IECON 2024). Chicago, USA, 2024.
  16. Kaneewar Ibrahim, Ricus Husmann, Sven Weishaupt and Harald Aschemann: Reinforcement Learning for Path Planning and Control of an Autonomous Vehicle with Collision Avoidance. 28th International Conference on System Theory, Control and Computing (ICSTCC) 2024, Sinaia, Romania.
  17. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Control of a Vapor Compression Cycle Based on a Moving-Boundary Model. 28th International Conference on System Theory, Control and Computing (ICSTCC) 2024, Sinaia, Romania.
  18. Sven Weishaupt, Ricus Husmann, Harald Aschemann, Nils Schlenther, Thimo Oehlschlaegel and Christian Steinbrecher: Comparative Analysis of Multiple Deep Reinforcement Learning Approaches For Collision-Free Path-Planning of a 3-DoF-Robot. 2024 American Control Conferene (ACC 2024), Toronto, Canada, 2024.
  19. Ricus Husmann, Sven Weishaupt and Harald Aschemann: Cascaded sliding-mode control of a vapor compression cycle. In 2023 27th International Conference on System Theory, Control and Computing (ICSTCC).
  20. Ricus Husmann, Sven Weishaupt and Harald Aschemann, H.: Nonlinear Control of a Vapor Compression Cycle by Input-Output Linearisation. In 2023 27th International Conference on Methods and Models in Automation and Robotics (MMAR), 193–198.
  21. Ricus Husmann and Harald Aschemann: Analysis and Qualitative Observability of two Vapor Compression Cycle Models, 2022 26th International Conference on System Theory, Control and Computing (ICSTCC), 2022, pp. 546–552.
  22. Ricus Husmann and Harald Aschemann, Harald: Dynamic Modeling of a Vapor Compression Cycle, IFAC-PapersOnLine, vol. 55, no. 20, pp. 523–528, 2022, 10th Vienna International Conference on Mathematical Modelling MATHMOD 2022.
  23. Ricus Husmann and Harald Aschemann: Cascaded NMPC for the Precise Position Control of a Pneumatic Actuator, 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021, Toronto, Canada.
  24. Ricus Husmann and Harald Aschemann: Comparison and Benchmarking of NMPC for Swing-Up and Side-Stepping of an Inverted Pendulum with Underlying Velocity Control, Third IFAC Conference on Modelling, Identification and Control of Nonlinear Systems, MICNON 2021, Tokyo, Japan.

 

 

     

Bücher, Sonderhefte und Buchbeiträge

  1. Sven Weishaupt, Kaneewar Ibrahim, Ricus Husmann and Harald Aschemann: Reinforcement Learning for Path Planning and  Control of an Autonomous Vehicle with Post-Training Tuning Abilities. In Algorithms for Machine Vision in Navigation and Control. Series Editors: Oleg Sergiyenko, Wendy Flores-Fuentes and Paolo Mercorelli. Springer Nature Switzerland, 2026.

Masterarbeiten

  1. Uphaus, Ole: Iterative und Lernende Verfahren für die Folgeregelung Nichtlinearer Systeme
  2. Grosche, Hannes: Echtzeitumsetzung von Algorithmen zur Kollisionsvermeidung für ein autonomes Fahrzeug
  3. Lange, Georg Paul: Nutzung von Daten einer Tiefenbildkamera zum Online-Lernen der Kinematik eines Mehrachsroboters
  4. Witte, Oliver: Sensororientierte Weiterentwicklung einer medizinischen Frischgasdosierung
  5. Ibrahim, Kaneewar: Kollisionsvermeidung für autonome Fahrzeuge auf Grundlage von Reinforcement-Learning-Methoden
  6. Weishaupt, Sven: Untersuchung von Reinforcement-Learning-Methoden für Robotik-Anwendungen
  7. Schmidt, Tom: NMPC-basierte Kollisionsvermeidung für ein autonomes Fahrzeug

 

Studienarbeiten

  1. Cao, Manh Duong: Untersuchung von Stochastischen Modellprädikativen Regelungsmethoden für Echtzeitanwendungen
  2. Lange, Georg Paul: Sensitivitätsbasierte Identifizierbarkeit von Parametern Nichtlinearer Systeme
  3. Weishaupt, Sven: Reglersynthese und simulative Validierung für Kompressionskältemaschinen

 

Bachelorarbeiten

  1. Bachmann, Jakob: Stabilisierende Regelung eines inversen Doppelpendels
  2. Woldt, Lucian: Nutzung von Gauß-Prozessen für die Online-Identifikation von nichtlinearer Reibung
  3. Lange, Georg Paul: Identifikation der Kinematik eines 6-Achs-Roboters

 

Projektarbeiten

  1. Grasnick, Sebastian; Kalla, Alexander: Inbetriebnahme  und Systemidentifikation eines Quadrocopters