AI 中文总结
本文针对腱驱动支撑型连续体机器人的闭链结构问题，提出主动任务空间刚度控制框架，经仿真和实验验证可提升抗负载能力与定位鲁棒性。
AI 中文摘要
支撑型连续体机器人（SCR）通过将操作型连续体机器人与支撑臂机械耦合，提升其承载能力，但其被动刚度由机械构型决定，无法在线调整以适配不同 payload（负载）或交互力，因此需要主动刚度控制来调节负载响应并保持定位精度。同时，闭链结构引入运动学约束，使任务空间调节和刚度控制复杂化。本文提出一种适用于腱驱动SCR的主动任务空间刚度控制框架。现有几何变量应变模型描述闭链动力学，该动力学被投影到与约束一致的运动子空间；投影滑模控制器调节操作臂末端，同时保留约束，通过李雅普诺夫分析建立闭环稳定性。位置调节后，基于位置误差反馈的虚拟笛卡尔弹簧引入主动表观刚度，以塑造力-位移响应。该框架在仿真中评估，并在规定外部负载和不同期望构型下进行实验验证。结果表明，增大指令刚度增益可减少负载引起的末端偏转，提高表观定向刚度，从而提升外部负载下的抗负载能力和定位鲁棒性。
英文摘要
Supportive continuum robots (SCRs) enhance the load-bearing capability of an operative continuum robot by mechanically coupling it with a supportive arm. However, their passive stiffness is determined by the mechanical configuration and cannot be adjusted online for varying payloads or interaction forces. Active stiffness control is therefore needed to regulate the load response and maintain positioning accuracy. Meanwhile, the closed-chain structure introduces kinematic constraints that complicate task-space regulation and stiffness control. This paper presents an active task-space stiffness control framework for a tendon-driven SCR. An existing geometric variable strain model describes the closed-chain dynamics, which are projected onto the constraint-consistent motion subspace. A projected sliding mode controller regulates the operative arm tip while preserving the constraints, and closed-loop stability is established through Lyapunov analysis. After position regulation, active apparent stiffness is introduced through a virtual Cartesian spring based on position-error feedback to shape the force--displacement response. The framework is evaluated in simulation and experimentally validated under prescribed external loads and different desired configurations. Results show that increasing the commanded stiffness gain reduces load-induced tip deflection and increases apparent directional stiffness, thereby improving load resistance and positioning robustness under external loading.
