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M.Sc. Jan Brüdigam

Technical University of Munich

Chair of Information-oriented Control (Prof. Hirche)

Postal address

Postal:
Barerstr. 21
80333 München


Short Biography

Since 08/2020 Research Assistant and PhD Candidate
Chair of Information-oriented Control (ITR)
Technical University of Munich, Germany (TUM)
09/2019 – 05/2020 Master Thesis: Variational Integrators in Maximal Coordinates
Stanford University, USA
2017 – 2020 Master of Science, Electrical and Computer Engineering
Focus: Robotics, Control Theory and Numerical Optimization
Technical University of Munich, Germany (TUM)
03/2017 – 09/2017 Bachelor Thesis: Control of Soft Exoskeletons
Harvard University, USA
2014 – 2017 Bachelor of Science, Electrical and Computer Engineering
Focus: Control Theory and Robotics
Technical University of Munich, Germany (TUM)

 

Research

ReHyb

Patients having suffered accidents or stroke often have to go through extensive rehabilitation to regain motor skills for an independent and self-determined life. In contrast to classical physical therapists, robotic rehabilitation systems are able to tirelessly and precisely apply intense manual labor over long periods of time, while accurately measuring performance and improvements of the patient.

As a Team of researchers at TUM and in collaboration with partners across Europe, for the ReHyb project we are developing the control of an upper-body exoskeleton using shared control strategies relying on model-based descriptions of the robotic system and data-driven system identification of the human. Our goal is to develop a patient-specific, assist-as-needed device for rehabilitation and daily living activities.

Shared Control

Increasing capabilities of modern robots allow for the handling of more and more complex tasks. Yet, this development does not at all replace humans since new opportunities arise for cooperative actions in complicated scenarios. In such settings, the human takes on a planning role while the robot is responsible for executing subtasks.

The combined effort of human and robot creates several interesting research questions. Here, a main focus lies in how to share control tasks between human and robot and how these shared control setups interact with one another. One example of human-robot interaction is the cooperation between exoskeleton and human within the ReHyb project.

Robotics in Maximal Coordinates

Typically, robotic systems are described in minimal (also called generalized) coordinates. Here, each coordinate represents a single degree of freedom of the underlying structure (for example the angle of a pendulum). The advantage of this parameterization lies in the small number of variables and the avoidance of constraints.

However, for modern robots carrying out complicated tasks minimal coordinates are not always ideal. Instead, it can be beneficial to use maximal coordinates basically resulting in a decoupled description of the system which can then be put together with additional constraints. This type of representation offers a number of numerical and control theoretic advantages. At the same time there are quite a few open questions still to be answered.

Code for a dynamics simulation in maximal coordinates can be found here:
https://github.com/janbruedigam/ConstrainedDynamics.jl

Student Projects and Theses

I am always looking for motivated students showing interest in my research. Feel free to reach out if you are interested in working on a thesis in my field of research, even if no open topics are listed below.

Please contact me by sending your transcript of records and resume (if available) so I can choose a topic matching your skills and background. Additionally, please let me know when you plan to start working on the thesis.

Open Theses

MA: Higher-Order Variational Integrators for Robotic Systems in Maximal Coordinates [PDF]
MA: Trajectory Optimization and Control in Maximal Coordinates [PDF]
IP+BA or MA: Numerically Efficient Control in Maximal Coordinates [PDF]

Publications

2020

  • J. Brüdigam and Z. Manchester: Linear-Time Variational Integrators in Maximal Coordinates. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2020 more… BibTeX Full text (mediaTUM)
  • J. Brüdigam and Z. Manchester: Linear-Quadratic Optimal Control in Maximal Coordinates. arXiv preprint: arXiv:2010.05886, 2020 more… BibTeX Full text (mediaTUM)