提出新型耦合动力学模型与双相机视觉伺服，提升无人机软体机械臂的控制精度与鲁棒性。
Strain-Parameterized Coupled Dynamics and Dual-Camera Visual Servoing for Aerial Continuum Manipulators
- 基于应变参数化柯西杆模型与无人机刚体模型，构建统一拉格朗日OED框架。
- 在真实原型上验证，系统可克服视角限制与姿态扰动，稳定跟踪目标。
- 适合研究无人机柔性机械臂控制、视觉伺服及多模态协同系统的科研人员。
腱驱动空中连续体机械臂（TD-ACMs）融合了无人飞行器（UAV）的机动性与轻量级连续体机器人（CR）的柔顺性。现有耦合动力学建模方法计算成本高，且未显式考虑飞行平台的欠驱动特性。本文提出一种具欠驱动基座的通用耦合动力学公式，将应变参数化柯西杆模型与无人机刚体模型统一纳入$ℝ(3)$上的拉格朗日常微分方程框架，避免高复杂度符号推导。基于该模型，设计了一种鲁棒双相机图像基视觉伺服（IBVS）方案，有效缓解传统方法的视场局限，补偿因无人机横向动力学引起的图像运动，并引入低层自适应控制器以应对建模不确定性，具有严格的稳定性保证。大量仿真与小型定制原型机实验表明，该框架在真实场景中表现出优异的有效性与鲁棒性。
原文摘要 · Abstract (English)
Tendon-driven aerial continuum manipulators (TD-ACMs) combine the maneuverability of uncrewed aerial vehicles (UAVs) with the compliance of lightweight continuum robots (CRs). Existing coupled dynamic modeling approaches for TD-ACMs incur high computational costs and do not explicitly account for aerial platform underactuation. To address these limitations, this paper presents a generalized dynamic formulation of a coupled TD-ACM with an underactuated base. The proposed approach integrates a strain-parameterized Cosserat rod model with a rigid-body model of the UAV into a unified Lagrangian ordinary differential equation (ODE) framework on $\mathrm{SE}(3)$, thereby eliminating computationally intensive symbolic derivations. Building upon the developed model, a robust dual-camera image-based visual servoing (IBVS) scheme is introduced. The proposed controller mitigates the field-of-view (FoV) limitations of conventional IBVS, compensates for attitude-induced image motion caused by UAV lateral dynamics, and incorporates a low-level adaptive controller to address modeling uncertainties with formal stability guarantees. Extensive simulations and experimental validation on a compact custom-built prototype demonstrate the effectiveness and robustness of the proposed framework in real-world scenarios.
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