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包含外力影响的机器人柔性手臂模型分析

Model Analysis of Robotic Soft Arms including External Force Effects.

作者信息

Chen Zhi, Liu Zhong, Han Xingguo

机构信息

School of Mechanical Engineering, Guilin University of Aerospace Technology, Guilin 541004, China.

出版信息

Micromachines (Basel). 2022 Feb 23;13(3):350. doi: 10.3390/mi13030350.

Abstract

Because robotic soft arms have a high power-to-weight ratio, low cost, and ease of manufacturability, increasing numbers of researchers have begun to focus on their characteristics in recent years. However, many urgent problems remain to be resolved. For example, soft arms are made of hyperelastic material, making it difficult to obtain accurate model predictions of the soft arm shape. This paper proposes a new modeling method for soft arms, combining the constant curvature model with Euler-Bernoulli beam theory. By combining these two modeling methods, we can quickly solve for the soft arm deformation under the action of an external force. This paper also presents an experimental platform based on a cable-driven soft arm to verify the validity of the proposed model. We carried out model verification experiments to test for different external effects. Experimental results show that the maximum error of our proposed soft arm deformation model is between 2.86% and 8.75%, demonstrating its effectiveness.

摘要

由于机器人软臂具有高功率重量比、低成本和易于制造的特点,近年来越来越多的研究人员开始关注其特性。然而,许多紧迫的问题仍有待解决。例如,软臂由超弹性材料制成,这使得难以获得软臂形状的准确模型预测。本文提出了一种软臂的新建模方法,将恒定曲率模型与欧拉 - 伯努利梁理论相结合。通过结合这两种建模方法,我们可以快速求解外力作用下软臂的变形。本文还提出了一个基于缆绳驱动软臂的实验平台,以验证所提出模型的有效性。我们进行了模型验证实验,以测试不同的外部效应。实验结果表明,我们提出的软臂变形模型的最大误差在2.86%至8.75%之间,证明了其有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49aa/8950771/bcde9cc998f7/micromachines-13-00350-g001.jpg

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