Dr. Carolina Passenberg
Control engineering @ Bosch Research –
We invent it for life
“As control engineer researchers, we bring cutting-edge control methods into the company and assess them for applicability to Bosch products. We cooperate closely with our business units in order to adapt our algorithms to the target systems. Our algorithms make Bosch products work at their maximum performance or they allow us to save costs by increasing calibration efficiency or extending component tolerances.”
In 2012, I started working in the control engineering research group @ Robert Bosch GmbH. I focus on model- based, adaptive and learning control methods ready for implementation on electronic control units. My colleagues and I already improved performance and calibration efficiency on real-world hydraulic, thermodynamic, and energy-generating systems and I am currently working on control algorithms for highly automated driving. I am glad for being part of Bosch, as Bosch allows me not only to do cutting-edge research but also to combine work and family life.
- Ph.D. dissertation on the control of haptic teleoperation systems, Dr.-Ing. @ TU Munich, GER
- Diploma in electrical and information technology, Dipl.-Ing. @ TU Munich, GER
- Graduation in electrical and computer engineering, M.Sc. @ Georgia Institute of Technology, USA
Robert Bosch GmbH (2014)Adaptive Druckregelung in einem Kraftstoffspeicher
- W. Kemmetmüller, J. Nitzsche, A. Sommerer, A. Trachte, D. Seiler-Thull, M. Bitzer, C. Passenberg, A. Kugi, K. Prinz
- DE 10 2013 208 867.1
Robert Bosch GmbH (2014)Druckregelung in einem Kraftstoffspeicher mit Vorsteuerung
- A. Trachte, D. Seiler-Thull, J. Nitzsche, W. Kemmetmüller, A. Sommerer, C. Passenberg, A. Kugi, M. Bitzer, K. Prinz
- DE 10 2013 208 869.8
C. Passenberg (2013)Transparency- and Performance-Oriented Control of Haptic Teleoperation Systems
- Ph.D. Dissertation, TU Munic
C. Passenberg et al. (2013)Exploring the Design Space of Haptic Assistants: The Assistance Policy Module
- C. Passenberg, A. Glaser, A. Peer
- IEEE Transactions on Haptics, vol. 6, issue 4
K. Prinz et al. (2013)Modellierung, Analyse und Regelung des Kraftstoffkreislaufs eines Diesel Common-Rail- Systems
- W. Kemmetmüller, C. Passenberg, A. Kugi, D. Seiler-Thul
- GMA FA 1.40
C. Passenberg et al. (2011)Towards real-time haptic assistance adaptation optimizing task performance and human effort
- R. Groten, A. Peer, M. Buss
- IEEE World Haptics Conference
A. Achhammer et al. (2010)Improvement of model-mediated teleoperation using a new hybrid environment estimation technique
- C. Weber, A. Peer
- IEEE International Conference on Robotics and Automation
C. Passenberg et al. (2010)Model-mediated teleoperation for multi-operator multi-robot systems
- A. Peer, M. Buss
- IEEE/RSJ International Conference on Intelligent Robots and Systems
C. Passenberg et al. (2010)A survey of environment- operator- and task-adapted controllers for teleoperation systems
- C. Passenberg, A. Peer, M. Buss
- Journal of Mechatronics: Special Issue on Design and Control Methodologies in Telerobotics, vol. 20, issue 7, p. 787-801
C. Weber et al. (2009)Position and force augmentation in a telepresence system and their effects on perceived realism
- V. Nitsch, U. Unterhinninghofen, B. Farber, M. Buss
- World Haptics
J. Wolff et al. (2007)Continuous Control Mode Transitions for Invariance Control of Constrained Nonlinear Systems
- C. Weber, M. Buss
- Proceedings of the 46th IEEE Conference on Decision and Control
Interview with Dr. Carolina Passenberg
Research Engineer Dynamic Systems and Control
Please tell us what fascinates you most about research.
Two main points fascinate me about research: first, it is going a step beyond state-of-the-art. And second, it is the look into the future. Regarding the first point, whenever you make a deep dive into a specific research topic, you will find open questions, unsolved problems, or a limited applicability. Finding a new approach or extending existing approaches to overcome some of the current limitations is exciting. Regarding the second point, doing research means not thinking about the next product generation but much further in the future. One example from my Ph.D. dissertation: I got the chance to remotely control a humanoid robot in Japan from Munich while receiving multi-modal feedback from that distant location. I saw through the “eyes” of the robot, I received audio feedback, I moved the legs of the robot by just walking around, and could handle objects with an on-site person by just moving the arms and grasping. I found it futuristic – like a look into the future.
What makes research done at Bosch so special?
Research @ Bosch is special, because we bring cutting-edge findings from academia to real-world products. So, I think we can be the link between academic research and the Bosch engineers. Our work has several facets: We want to find and adapt methods suitable for Bosch components or systems. Control algorithms are required in diverse applications ranging from electrical over mechanical and hydraulic to thermodynamic systems. This makes our work diverse and fascinating. We have to show that the methods meet the performance requirements of the target system and that they can cope with the given, limited computing power and memory. We also have to prove that the methods are beneficial compared to what we already have, and we have to show the benefits on the real-world component or system, not just in simulation. This makes our work challenging. It is important for us to enable our colleagues in the business units to implement and apply our results. This makes our work valuable and relevant.
What research topics are you currently working on at Bosch?
I am currently working on model predictive methods for highly automated driving.
What are the biggest scientific challenges in your field of research?
The biggest scientific challenges in control engineering arise in the area of connectivity, autonomous driving and smart things, and the acceleration of the development process. Connectivity means that we have to deal with deficient communication channels and multi-agent systems. Autonomous driving and smart systems/things require the system to dynamically adapt to unknown situations, unknown environments, or varying user behavior. The increasing speed in the development process places high demands on the quality and flexibility of the model-based controller. Our current methods of research are therefore networked control systems, optimal control including model-predictive control, and adaptive and learning control. From an engineering point of view, we aim at providing robust, high-quality, and flexible controllers.
How do the results of your research become part of solutions "Invented for life"?
Whenever our colleagues in the business units take over our results, implement them in software, and make these software features ready for series production, our research results become parts of products “invented for life.” The nice thing about control is that we can apply it to almost any dynamical system. And that is what we do: we cooperate with many business units from mobility solutions over industrial technology to energy and building technology and apply our methods to diverse components and systems. And this again means that our results become part of many different Bosch products.