Characterization and nonlinear models of bending extensile/contractile pneumatic artificial muscles

弯曲 气动人工肌肉 材料科学 执行机构 弯矩 非线性系统 软机器人 曲率 灵活性(工程) 夹持器 人工肌肉 机械工程 结构工程 计算机科学 工程类 人工智能 物理 几何学 数学 统计 量子力学
作者
Qinghua Guan,Jian Sun,Yanju Liu,Norman M. Wereley,Jinsong Leng
出处
期刊:Smart Materials and Structures [IOP Publishing]
卷期号:30 (2): 025024-025024 被引量:17
标识
DOI:10.1088/1361-665x/abd4b0
摘要

Abstract Pneumatic artificial muscles (PAMs) are compliant fluidic actuators, usually consisting of a tubular bladder, a braided sleeve and end fittings. PAMs have been studied extensively by researchers; however, most previous researches are focused on the axial PAMs. Herein, a pair of nonlinear models were developed based on the principle of virtual work and the force balance analysis. And the two models are applicable to both bending extensile PAMs (BE-PAMs) and bending contractile PAMs (BC-PAMs). In this study, a cyclic bending moment loading experimental method were proposed and conducted with BE-PAMs and BC-PAMs to characterize their deformation and actuation performance and draw their overall relationships of actuation moment to bending curvature and inner pressure. With the experimental results, the validation analysis was carried out to demonstrate the validity of the two models. The energy model can get higher accuracy, while the force balance model could provide more details of the interior and interaction stress conditions. The combination of both can promote the comprehension of non-axial bending PAMs. Moreover, two three-finger soft grippers and a humanoid hand based on BE-PAMs and BC-PAMs were built and tested to investigate their performance on gripping objects. The BE-PAM gripper showed more accommodative gripping performance, whereas, the BC-PAM gripper owned higher gripping force. The humanoid hand combining the merits of both showed excellent flexibility, adaptability and decent load capability in gripping object with various sizes, shapes and materials.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
谨慎溪流发布了新的文献求助10
1秒前
喃喃发布了新的文献求助10
1秒前
1秒前
1秒前
方春荣发布了新的文献求助10
1秒前
1秒前
lasfjas完成签到,获得积分10
1秒前
悄悄发布了新的文献求助10
2秒前
安若发布了新的文献求助10
2秒前
2秒前
2秒前
4秒前
多多发布了新的文献求助10
4秒前
really_1896发布了新的文献求助10
4秒前
搜集达人应助聪慧念柏采纳,获得10
4秒前
Daryl发布了新的文献求助30
4秒前
膝膝相关完成签到,获得积分10
5秒前
ssos发布了新的文献求助10
5秒前
多情易蓉发布了新的文献求助10
5秒前
舍不得你发布了新的文献求助10
5秒前
6秒前
wanci应助上上签采纳,获得10
6秒前
6秒前
6秒前
大雪纷飞发布了新的文献求助10
6秒前
7秒前
1433223发布了新的文献求助10
7秒前
怡然铃铛发布了新的文献求助10
7秒前
枫叶完成签到,获得积分10
7秒前
酷波er应助xhl采纳,获得10
7秒前
笨笨的秋蝶完成签到,获得积分10
8秒前
8秒前
8秒前
9秒前
完美世界应助一介书生采纳,获得10
9秒前
渡人舟应助神速闪电采纳,获得10
10秒前
mxdckd完成签到,获得积分10
10秒前
10秒前
10秒前
11秒前
高分求助中
Les chinois de jakarta: temples et vie collective 1000
Autoparametric Resonance in Mechanical Systems 1000
Social Psychology 800
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 800
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 600
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7648375
求助须知:如何正确求助?哪些是违规求助? 9221094
关于积分的说明 19792690
捐赠科研通 7214003
什么是DOI,文献DOI怎么找? 3277866
关于科研通互助平台的介绍 2438921
邀请新用户注册赠送积分活动 2276132