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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.18720 |
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| _version_ | 1866914578587189248 |
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| author | Hansen, Harald Minde Sæbø, Bjørn Kåre Pettersen, Kristin Y. Gravdahl, Jan Tommy Di Castro, Mario |
| author_facet | Hansen, Harald Minde Sæbø, Bjørn Kåre Pettersen, Kristin Y. Gravdahl, Jan Tommy Di Castro, Mario |
| contents | Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. This paper presents a comparative study of data-driven system identification methods, including N4SID, ARX, and SINDYc, for modeling a tendon-actuated continuum robot with rolling joints developed at CERN. Despite the high number of joints of the robot, experimental analysis reveals that a two-degree-of-freedom dynamic model can accurately capture the system dynamics, owing to strong kinematic dependencies between the joints. The models are validated against experimental data, and used in the design of a model predictive controller, demonstrating their feasibility for real-time control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_18720 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Data-Driven Dynamic Modeling of a Tendon-Actuated Continuum Robot Hansen, Harald Minde Sæbø, Bjørn Kåre Pettersen, Kristin Y. Gravdahl, Jan Tommy Di Castro, Mario Robotics Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. This paper presents a comparative study of data-driven system identification methods, including N4SID, ARX, and SINDYc, for modeling a tendon-actuated continuum robot with rolling joints developed at CERN. Despite the high number of joints of the robot, experimental analysis reveals that a two-degree-of-freedom dynamic model can accurately capture the system dynamics, owing to strong kinematic dependencies between the joints. The models are validated against experimental data, and used in the design of a model predictive controller, demonstrating their feasibility for real-time control. |
| title | Data-Driven Dynamic Modeling of a Tendon-Actuated Continuum Robot |
| topic | Robotics |
| url | https://arxiv.org/abs/2605.18720 |