TMP origami jumping mechanism with nonlinear stiffness

跳跃的 非线性系统 刚度 跳跃 控制理论(社会学) 结构工程 材料科学 机械工程 机械 纳米技术 计算机科学 工程类 物理 人工智能 控制(管理) 地质学 古生物学 量子力学
作者
Sahand Sadeghi,Samuel Allison,Blake Bestill,Suyi Li
出处
期刊:Smart Materials and Structures [IOP Publishing]
卷期号:30 (6): 065002-065002 被引量:6
标识
DOI:10.1088/1361-665x/abf5b2
摘要

Abstract Via numerical simulation and experimental assessment, this study examines the use of origami folding to develop robotic jumping mechanisms with tailored nonlinear stiffness to improve dynamic performance. We propose a multifunctional structure where the load-carrying skeleton of the structure acts as the energy-storage medium at the same time. Specifically, we use Tachi–Miura polyhedron (TMP) bellow origami—which exhibits a nonlinear ‘strain-softening’ force-displacement curve—as a jumping robotic skeleton with embedded energy storage. TMP’s nonlinear stiffness allows it to store more energy than a linear spring and offers improved jumping height and airtime. Moreover, the nonlinearity can be tailored by directly changing the underlying TMP crease geometry. A critical challenge is to minimize the TMP’s hysteresis and energy loss during its compression stage right before jumping. So we used the plastically annealed lamina emergent origami (PALEO) concept to modify the TMP creases. PALEO increases the folding limit before plastic deformation occurs, thus improving the overall strain energy retention. Jumping experiments confirmed that a nonlinear TMP mechanism achieved roughly 9% improvement in air time and a 13% improvement in jumping height compared to a ‘control’ TMP sample with a relatively linear stiffness. This study’s results validate the advantages of using origami in robotic jumping mechanisms and demonstrate the benefits of utilizing nonlinear spring elements for improving jumping performance. Therefore, they could foster a new family of energetically efficient jumping mechanisms with optimized performance in the future.

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
刚刚
Hey关闭了Hey文献求助
刚刚
学渣向下完成签到,获得积分10
刚刚
咚咚咚发布了新的文献求助10
刚刚
1秒前
willen完成签到,获得积分10
1秒前
1秒前
奇怪的柒完成签到,获得积分10
2秒前
2秒前
2秒前
3秒前
文静的枫叶完成签到,获得积分10
3秒前
科目三应助神麒小雪采纳,获得10
3秒前
zzznznnn发布了新的文献求助10
4秒前
pbf发布了新的文献求助20
4秒前
科研通AI5应助有风采纳,获得10
5秒前
Lin完成签到,获得积分10
5秒前
科研通AI5应助肉松小贝采纳,获得10
6秒前
粉色完成签到,获得积分10
6秒前
Ll发布了新的文献求助10
6秒前
6秒前
愉快彩虹发布了新的文献求助10
7秒前
CTL完成签到,获得积分10
7秒前
7秒前
共享精神应助加减乘除采纳,获得10
7秒前
7秒前
恬恬完成签到,获得积分10
7秒前
8秒前
22发布了新的文献求助10
8秒前
aacc956发布了新的文献求助10
8秒前
8秒前
谨慎涵柏完成签到,获得积分10
9秒前
快乐的如风完成签到,获得积分10
10秒前
11秒前
吃猫的鱼完成签到,获得积分10
11秒前
脑洞疼应助润润轩轩采纳,获得10
12秒前
刘文静完成签到,获得积分10
13秒前
Southluuu发布了新的文献求助10
13秒前
chenjyuu发布了新的文献求助10
13秒前
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527699
求助须知:如何正确求助?哪些是违规求助? 3107752
关于积分的说明 9286499
捐赠科研通 2805513
什么是DOI,文献DOI怎么找? 1539954
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709759