基于结构重构的平面移动索驱动并联机器人刚度调制

Adhiti Raman, Matthias J. Schmid, V. Krovi
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引用次数: 4

摘要

移动索驱动并联机械臂(m-CDPM)是基于基础绞车的机动性而具有更强能力(抗索张力和可重构性)的一类并联机械臂。在过去的工作中,我们还探索了可调节弹簧刚度模块的创建,该模块与电缆一致,可以解耦电缆刚度和电缆张力。所有这些内部自由度使m-CDPM能够在平衡末端执行器扳手和提高横向干扰抑制能力的同时跟踪所需的轨迹。然而,参数和配置的选择是释放这些好处的关键。为此,我们考虑了一种将任务执行划分为主要(快速)绞车张力控制和次要(缓慢)重构和关节刚度调制的方法。这将使主要的轨迹跟踪任务与次要的任务空间刚度裁剪结合起来,使用系统重构和关节刚度调制。在本文中,我们将范围限制在可行性评估,以实现刚度调制作为离线设计优化设置中的次要目标(但着眼于实时实现)。这些方面在3-PRP m-CDPM的背景下进行说明,用于在扳手可行的工作空间内跟踪所需的轨迹。次要任务是刚度椭球的方向对准和整形,以塑造沿轨迹的抗扰特性。通过非线性工作空间可行性约束下的多目标加权代价函数约束最小化,以及不等式刚度和张力约束来求解优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stiffness Modulation for a Planar Mobile Cable-Driven Parallel Manipulators via Structural Reconfiguration
Mobile Cable-Driven Parallel Manipulators (m-CDPM) are a sub-class of CDPM with greater-capabilities (antagonistic cable-tensioning and reconfigurability) by virtue of mobility of the base-winches. In past work, we had also explored creation of adjustable spring-stiffness modules, in-line with cables, which decouple cable-stiffness and cable-tensions. All these internal-freedoms allow an m-CDPM to track desired trajectories while equilibrating end-effector wrenches and improving lateral disturbance-rejection. However, parameter and configuration selection is key to unlocking these benefits. To this end, we consider an approach to partition task-execution into a primary (fast) winch-tension control and secondary (slow) reconfiguration and joint-stiffness modulation. This would enable a primary trajectory-tracking task together with secondary task-space stiffness tailoring, using system-reconfiguration and joint-stiffness modulation. In this paper, we limit our scope to feasibility-evaluation to achieve the stiffness modulation as a secondary goal within an offline design-optimization setting (but with an eye towards real-time implementation). These aspects are illustrated in the context of a 3-PRP m-CDPM for tracking a desired trajectory within its wrench-feasible workspace. The secondary-task is the directional-alignment and shaping of the stiffness ellipsoid to shape the disturbance-rejection characteristics along the trajectory. The optimization is solved through constrained minimization of a multi-objective weighted cost function subject to non-linear workspace feasibility, and inequality stiffness and tension constraints.
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