ConcentricTube Robots (CTRs)
Schematic of a three-tube CTR
Electrical CTR actuation system for three tubes
Test stand with an actuation system mounted inside a photogrammetric system
Objective of the project
- Development of a hybrid model for CTR motion prediction, mapping cannula configurations
- Simultaneous cannula design and global trajectory planning via multi-objective optimization
- Reinforcement Learning/Model predictive control based self-sensing feedback control for guidance of CTR cannula
- Delivery of a demonstrator integrating hardware, software, and a methodological framework to show this AI-based design assistance approach within a surgical workflow
Workflow for the holistic AI-based design assistance system
Preliminary work inside the SPP
- Hardware preparation
- Research on different CTR actuation systems regarding high positioning accuracy
- Build-up of a fully-automated, high-precision photogrammetric measurement system
- Research on shape-setting thermal processes of the tubes and their influence on the tubes’ behavior
- Development of a marker-free 3d shape reconstruction algorithm for continuum robots
- Data-driven modeling
- Establishment of a data-driven forward kinematic model for CTR shape prediction
- Exploration of data expansion using generative adversarial networks
Preliminary work outside the SPP
- Self-sensing control strategy
- Basic considerations of a possible application of CTCRs in the field of stereotactic neurosurgery
- Many years of ongoing research in the field of continuum robots regarding actuation system development, medical applications, modelling, path planning, and control.
How can we support other projects?
- Database of 3D backbone measurements of the CTR
- Exchange of knowledge on modelling nonlinear Cosserat continuum mechanics
- Multiobjective optimization methods (knowledge and software)
- AI-methods for (sub)modules, for inverse problems, etc
How could other projects support our work?
- Exchange on physics-based machine learning approaches
- Exchange on hybrid techniques for multiobjective optimization
- Exchange on AI-based design approaches, e.g. genetic algorithms
- Exchange on AI-based control
First Phase Publications
- Hoffmann, M. K.; Gulakala, R.; Mühlenhoff, J.; Ding, Z.; Sattel, T.; Stoffel, M.; Flaßkamp, K.: Data augmentation for design of concentric tube continuum robots by generative adversarial networks. Proceedings in Applied Mathematics and Mechanics, 23, e202300278, 2023. DOI: 10.1002/pamm.202300278
- Payrebrune, K. de; Flasskamp, K.; Ströhla, T.; Sattel, T.; Bestle, D.; Röder, B.; Eberhard, P.; Peitz, S.; Stoffel, M.; Gulakala, R.; Borse, A.; Wohlleben, M.; Sextro, W.; Raff, M.; Remy, C. D.; Yadav, M.; Stender, M.; Delden, J. van; Lüddecke, T.; Langer, S. C.; Schultz, J.; Blech, C. (2024). The Impact of AI on Engineering Design Procedures for Dynamical Systems. Technische Mechanik - European Journal of Engineering Mechanics, 45(1), DOI: 10.24352/UB.OVGU-2025-037.
- Muehlenhoff, J., Hoffmann, M. K., Keiner, D., Henia, M., Oertel, J., Flasskamp, K., & Sattel, T. (2024, June). A toolchain for deployment of concentric tube continuum robots as curved cannulae in stereotactic neurosurgery. In ACTUATOR 2024; International Conference and Exhibition on New Actuator Systems and Applications (pp. 252-255). VDE.
Contact
Prof. Dr.-Ing. Jürgen Maas
Technische Universität Berlin
Institut für Maschinenkonstruktion und Systemtechnik
Fachgebiet Elektromechanische Konstruktionen
Hardenbergstraße 36
10623 Berlin
Email: juergen.maas@tu-berlin.de
Prof. Dr. Joachim Örtel
Universitätsklinikum des Saarlandes
Klinik für Neurochirurgie
Kirrberger Straße 90.5
66424 Homburg
Email: joachim.oertel@uks.eu
Prof. Dr.-Ing. Thomas Sattel
Technische Universität Ilmenau
Fakultät Maschinenbau
Fachgebiet Mechatronik
Max-Planck-Ring 12
98693 Ilmenau
Email: thomas.sattel@tu-ilmenau.de
Abd Elkarim Masoud
Email: abdelkarim.masoud@emk.tu-berlin.de
Zhaoheng Ding
Email: zhaoheng.ding@tu-ilmenau.de
Julian Mühlenhoff
Email: julian.muehlenhoff@tu-ilmenau.de