ArticleIEEE robotics and automation letters2025
Deep Koopman Approach for Nonlinear Dynamics and Control of Tendon-Driven Continuum Robots.
Article in IEEE robotics and automation letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Interleaved Imaging and Actuation for Real-Time MRI During Active Control of a Magnetically-Actuated Robotic Catheter.IEEE transactions on bio-medical engineering · 2026Article
- Koopman global linearization of contact dynamics for robot locomotion and manipulation enables elaborate control.Nature communications · 2026Article
- On Integrating Friction Dynamics Into Cosserat Models for Tendon-Driven Continuum Manipulators.IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division · 2026Article
- Few-Shot Physics-Informed Neural Network for Shape Reconstruction of Concentric-Tube Robots.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation · 2026Article
- Error-State Model Predictive Path Integral Control of Tendon-Driven Continuum Robots using Cosserat Rod Dynamics with Strain Parametrization.IEEE robotics and automation letters · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
Tendon-driven continuum robots (TDCRs) have received widespread attention in the medical domain due to their slender shape and flexibility. Modeling the dynamics of TDCRs involves continuum mechanics that result in nonlinear and computationally intensive models posing challenges for real-time control. In this work, we propose efficient, and controloriented modeling of the nonlinear dynamics of TDCRs leveraging the deep Koopman approach. This method transforms the states of the system into an intrinsic nonlinear manifold, where the autonomous dynamics are approximated linearly, and the actuation input enters the system with a bilinear term. The proposed model captures the nonlinearities, including space-dependent variations in the system spectrum. Position control is implemented using a linear quadratic controller, leveraging the linear nature of the Koopman operator. The accuracy of the proposed method is experimentally validated using a dualtendon robotic steerable catheter, achieving a position tracking error of 1.64 mm (SD = 0.74) for multi-sinusoidal, and 0.60 mm (SD = 0.30) for sinusoidal (0.05 Hz) target trajectories. The results demonstrate the potential for applying the proposed approach for real-time control of a broad range of TDCRs.
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