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Toward Modular Active-Cell Robots (MACROs): SMA Cell Design and Modeling of Compliant, Articulated Meshes

机译:迈向模块化主动细胞机器人(MACRO):符合要求的铰接式网格物体的SMA细胞设计和建模

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In this paper, we present the design of a shape-memory-alloy (SMA)-based compliant linear actuator [active cell (AC)] and the use of these in designing and modeling articulated meshes, which form the mechanical subsystem of a class of proposed modular active-cell robots (MACROs). The ACs are capable of undergoing ∼25% strain and groups of cells are connected via passively compliant nodes to produce articulated mesh networks. The deformation of compliant meshes of ACs is modeled by scale-invariant parametric equations derived from the physics of SMA deformations and a reduced-order model of the cells. Parameters of the implemented system were used to develop a simulation platform that predicts the mechanical deformation of the networked robot given electrical inputs at arbitrary nodes of the network. We provide results of several experimental trials used to validate and establish the accuracy of this deformation model. The error in predicting deformations in small meshes is shown to be under 10% over both time-varying inputs and at steady states.
机译:在本文中,我们介绍了基于形状记忆合金(SMA)的线性执行器[Active cell(AC)]的设计,以及在设计和建模铰接式网格中的应用,这些构成了一类机械子系统提出的模块化有源细胞机器人(MACRO)。 AC能够承受约25%的应变,并且单元组通过无源顺应性节点连接以产生铰接式网格网络。通过从SMA变形的物理原理和单元的降阶模型得出的尺度不变参数方程对AC的顺应网格的变形进行建模。所实现系统的参数用于开发一个仿真平台,该仿真平台在给定网络中任意节点的电输入的情况下预测联网机器人的机械变形。我们提供了一些用于验证和建立此变形模型准确性的实验结果。在时变输入和稳态下,预测小网格变形的误差均低于10%。

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