A Static Modeling Method Considering Friction for the Shape Prediction or Force Sensing of Concentric Cable-Driven Manipulators

作者：Zonggao Mu, Yuming Gao, Weitao Li, Guikun Lv, Shun Zhao, Ruichun Dong · 发表于：IEEE Transactions on Automation Science and Engineering · 年份：2024 · DOI：10.1109/tase.2024.3408916 · 被引用次数：7 · 研究领域：Soft Robotics and Applications、Robot Manipulation and Learning、Robotic Mechanisms and Dynamics

Owing to the flexibility and redundancy, concentric cable-driven manipulators are widely used in confined space applications. However, it is challenging to establish shape prediction or force sensing for this type of manipulator. This paper proposes a static modeling method to address the shape prediction or force sensing challenges of concentric cable-driven manipulators. The Newton-Euler method is adopted to establish the static model of the concentric cable-driven manipulator with consideration of friction. On the one hand, the static model can accurately predict the shape when the external load and cable tension of the concentric cable-driven manipulator are known. On the other hand, the static model can also assist force sensing when the cable tension and shape of the concentric cable-driven manipulator are known. Finally, the accuracy of the shape prediction and force sensing of this model are both verified by experiment, separately. The results show that the accuracy of shape prediction is 95% and the accuracy of force sensing is 90%. The model is thus suitable for the shape prediction or force sensing of the concentric cable-driven manipulator. In addition, the errors associated with shape prediction or force sensing were found to be significantly reduced when the influence of friction was taken into account. Therefore, the proposed static modeling method considering friction is effective for the shape prediction or force sensing of concentric cable-driven manipulator...