用克拉克变换构建腱驱动连续机器人动态模型，实现精准实时控制。
Toward Dynamic Control of Tendon-driven Continuum Robots using Clarke Transform
- 基于克拉克变换与欧拉-拉格朗日方法建立二维流形上的动态模型。
- 在单段五腱物理原型上实现精确轨迹跟踪与抗干扰控制。
- 无需增加控制器复杂度即可提升力分布与刚性，适合多腱冗余设计。
本文提出一种针对多段、每段任意数量腱的腱驱动连续机器人（TDCRs）的动态模型与控制框架。通过结合克拉克变换、欧拉-拉格朗日形式化及分段恒曲率假设，在关节空间嵌入的二维流形上建立满足腱约束的动态模型。设计了线性与约束感知控制器，直接作用于该流形，并提出实用方法避免负腱力而不牺牲控制精度。该方法为过驱动TDCRs提供了新的设计可能，可在不增加控制器复杂度的前提下改善力分布与刚性。在仿真与单段五腱物理原型上验证，系统在实时条件下表现出准确动态行为与鲁棒轨迹跟踪能力。
原文摘要 · Abstract (English)
In this paper, we propose a dynamic model and control framework for tendon-driven continuum robots (TDCRs) with multiple segments and an arbitrary number of tendons per segment. Our approach leverages the Clarke transform, the Euler-Lagrange formalism, and the piecewise constant curvature assumption to formulate a dynamic model on a two-dimensional manifold embedded in the joint space that inherently satisfies tendon constraints. We present linear and constraint-informed controllers that operate directly on this manifold, along with practical methods for preventing negative tendon forces without compromising control fidelity. This opens up new design possibilities for overactuated TDCRs with improved force distribution and stiffness without increasing controller complexity. We validate these approaches in simulation and on a physical prototype with one segment and five tendons, demonstrating accurate dynamic behavior and robust trajectory tracking under real-time conditions.
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