Article(id=1246031926918754630, tenantId=1146029695717560320, journalId=1241755870837649424, issueId=1246031922707677827, articleNumber=null, orderNo=null, doi=10.19636/j.cnki.cjsm42-1250/o3.2024.014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710345600000, receivedDateStr=2024-03-14, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1775006761531, onlineDateStr=2026-04-01, pubDate=1724515200000, pubDateStr=2024-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775006761531, onlineIssueDateStr=2026-04-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775006761531, creator=13701087609, updateTime=1775006761531, updator=13701087609, issue=Issue{id=1246031922707677827, tenantId=1146029695717560320, journalId=1241755870837649424, year='2024', volume='45', issue='4', pageStart='427', pageEnd='564', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1775006760527, creator=13701087609, updateTime=1775006830786, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1246032217470779944, tenantId=1146029695717560320, journalId=1241755870837649424, issueId=1246031922707677827, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1246032217470779945, tenantId=1146029695717560320, journalId=1241755870837649424, issueId=1246031922707677827, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=477, endPage=487, ext={EN=ArticleExt(id=1246031928940409160, articleId=1246031926918754630, tenantId=1146029695717560320, journalId=1241755870837649424, language=EN, title=Asymmetric Bristle Model for Steel Brush and Its Application, columnId=1244229834482757770, journalTitle=Chinese Journal of Solid Mechanics, columnName=Research Paper, runingTitle=null, highlight=null, articleAbstract=

In this paper, an asymmetric bristle model based on the combination of bristle model and LuGre model is proposed to explain the direction-dependent friction (i.e., asymmetric friction) phenomenon exhibited by steel brushes. In this model, friction is generated through the horizontal frictionless contact between asymmetric bristles and the contacted substrate. Numerical simulation and expreimental results demonstrate that the asymmetric bristle model can effectively illustrate the direction-dependent friction phenomenon. Furthermore, in a simulation study of a planar biped robot, results show that applying this model can improve the maximum motion speed of the planar biped robot compared to using a symmetric friction model. Additionally, exmprimental resutls indicate that compared to rubber materials, steel brushes possess the advantages of high friction and abrasion resistance. Therefore, due to these propterties, steel brush structures may have great application prospects and potential benefits in the field of legged robotics.

, correspAuthors=Zhilong Huang, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Weixiang Zhong, Yongbin Jin, Xiaoling Jin, Ronghao Bao, Zhilong Huang), CN=ArticleExt(id=1246031938700554891, articleId=1246031926918754630, tenantId=1146029695717560320, journalId=1241755870837649424, language=CN, title=适用于钢丝毛刷的非对称鬃毛模型及应用, columnId=1241831201896469478, journalTitle=固体力学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

本文针对钢丝毛刷表现出的方向依赖性摩擦现象(非对称摩擦),提出了一种基于鬃毛模型和LuGre模型的非对称鬃毛模型,其摩擦力由非对称刷毛与被接触基底之间水平方向相互无摩擦接触产生的. 数值模拟和实验研究表明:非对称鬃毛模型能很好地说明方向依赖性摩擦现象,并在平面双足机器人的仿真研究中发现,与对称摩擦模型相比,此模型能提高机器人最大运动速度. 此外,实验研究表明钢丝毛刷相比于橡胶材质具有高摩擦、高耐磨等优势. 基于这些特性,钢丝毛刷结构在足式机器人领域有着较大的应用前景和潜在优势.

, correspAuthors=黄志龙, authorNote=null, correspAuthorsNote=
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Value of parameter identification for steel brush in form of 2*2

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σ(m-1σ0σ1σ2(s)θc(m-1θs(m-1ωsc(rad/s)
226.451.649.96×10-26.96×10-3125.82142.421.28
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2*2形式的钢丝毛刷参数识别数值

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σ(m-1σ0σ1σ2(s)θc(m-1θs(m-1ωsc(rad/s)
226.451.649.96×10-26.96×10-3125.82142.421.28
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Value of parameter identification for different contact pairs

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Materialsσ(m-1σ0σ1σ2(s)θc(m-1θs(m-1ωsc(rad/s)
Aluminum226.451.649.96×10-26.96×10-3125.82142.421.28
Nylon179.540.901.05×10-21.00×10-6115.35135.091.94
Ceramic244.991.911.03×10-29.67×10-459.3487.022.18
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不同接触对参数识别数值

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Materialsσ(m-1σ0σ1σ2(s)θc(m-1θs(m-1ωsc(rad/s)
Aluminum226.451.649.96×10-26.96×10-3125.82142.421.28
Nylon179.540.901.05×10-21.00×10-6115.35135.091.94
Ceramic244.991.911.03×10-29.67×10-459.3487.022.18
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Typical parameters of a simplified dynamic model for a single leg of a planar biped robot

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平面双足机器人简化动力学模型单条腿的典型参数

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7.52.00.280.10.0160.010.050.050.60.30.33535
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适用于钢丝毛刷的非对称鬃毛模型及应用
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钟炜翔 , 金永斌 , 金肖玲 , 鲍荣浩 , 黄志龙 **
固体力学学报 | 研究论文 2024,45(4): 477-487
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固体力学学报 | 研究论文 2024, 45(4): 477-487
适用于钢丝毛刷的非对称鬃毛模型及应用
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钟炜翔, 金永斌, 金肖玲, 鲍荣浩, 黄志龙**
作者信息
  • 浙江大学航空航天学院,杭州,310000

通讯作者:

** E-mail:.
Asymmetric Bristle Model for Steel Brush and Its Application
Weixiang Zhong, Yongbin Jin, Xiaoling Jin, Ronghao Bao, Zhilong Huang**
Affiliations
  • School of Aeronautics and Astronautics, Zhejiang University, Hangzhou, 310027
出版时间: 2024-08-25 doi: 10.19636/j.cnki.cjsm42-1250/o3.2024.014
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本文针对钢丝毛刷表现出的方向依赖性摩擦现象(非对称摩擦),提出了一种基于鬃毛模型和LuGre模型的非对称鬃毛模型,其摩擦力由非对称刷毛与被接触基底之间水平方向相互无摩擦接触产生的. 数值模拟和实验研究表明:非对称鬃毛模型能很好地说明方向依赖性摩擦现象,并在平面双足机器人的仿真研究中发现,与对称摩擦模型相比,此模型能提高机器人最大运动速度. 此外,实验研究表明钢丝毛刷相比于橡胶材质具有高摩擦、高耐磨等优势. 基于这些特性,钢丝毛刷结构在足式机器人领域有着较大的应用前景和潜在优势.

非对称摩擦  /  鬃毛模型  /  LuGre模型  /  平面双足机器人

In this paper, an asymmetric bristle model based on the combination of bristle model and LuGre model is proposed to explain the direction-dependent friction (i.e., asymmetric friction) phenomenon exhibited by steel brushes. In this model, friction is generated through the horizontal frictionless contact between asymmetric bristles and the contacted substrate. Numerical simulation and expreimental results demonstrate that the asymmetric bristle model can effectively illustrate the direction-dependent friction phenomenon. Furthermore, in a simulation study of a planar biped robot, results show that applying this model can improve the maximum motion speed of the planar biped robot compared to using a symmetric friction model. Additionally, exmprimental resutls indicate that compared to rubber materials, steel brushes possess the advantages of high friction and abrasion resistance. Therefore, due to these propterties, steel brush structures may have great application prospects and potential benefits in the field of legged robotics.

asymmetric friction  /  bristle model  /  LuGre model  /  planar biped robot
钟炜翔, 金永斌, 金肖玲, 鲍荣浩, 黄志龙. 适用于钢丝毛刷的非对称鬃毛模型及应用. 固体力学学报, 2024 , 45 (4) : 477 -487 . DOI: 10.19636/j.cnki.cjsm42-1250/o3.2024.014
Weixiang Zhong, Yongbin Jin, Xiaoling Jin, Ronghao Bao, Zhilong Huang. Asymmetric Bristle Model for Steel Brush and Its Application[J]. Chinese Journal of Solid Mechanics, 2024 , 45 (4) : 477 -487 . DOI: 10.19636/j.cnki.cjsm42-1250/o3.2024.014
摩擦是一种常见的物理现象,通常用来描述物体表面之间的相互作用. 目前存在很多摩擦模型用来描述摩擦现象,比较经典的模型如库仑摩擦模型、Stribeck摩擦模型等[1]. 此外,Dahl在1977年提出了Dahl模型[2-5],其通过观察发现在摩擦力未达到最大静摩擦力之前,接触界面间存在微小位移,即预滑动位移,并将此状态下的摩擦行为假设为一种类似弹簧特性的动态摩擦模型,Dahl模型不仅描述了库仑摩擦现象,还描述了预滑动、可变静摩擦、摩擦滞后等现象. Haessig和Friedland于1991年提出了鬃毛模型[6],该模型从微观角度描述了接触界面间的随机行为,可以较为准确地捕捉微观摩擦的随机特性. 随后,Canudas de Wit于1995年在Dahl模型的基础上提出了LuGre模型[7],该模型同时采用了鬃毛模型的思想,用鬃毛的平均变形量进行建模,LuGre模型除了包含Dahl模型和鬃毛模型的优点外,还可以描述Stribeck效应、粘性摩擦等现象,其中Stribeck效应是指在相对滑动速度较低时,摩擦力随着相对速度的增加反而下降,即摩擦力-速度曲线出现负斜率[8].
在实际结构中存在方向依赖性的摩擦现象,也称非对称摩擦,即,当外部切向力施加在物体一个方向时,物体会很容易地相对于其所接触的另一个物体移动,而在相反方向上则很难移动,比如蛇利用腹部的鳞片进行爬行[9-11]. 非对称摩擦现象在许多生物体表面可以广泛观察到,这些生物表面具有各向异性的微结构排列,如瓢虫腿上的毛状粘附刚毛[12]、蛇皮上鳞片的微观排列分布[13]. 生物体利用这些各向异性结构产生的非对称摩擦,从而实现在特定方向上的运动.
除了这些仿生学研究外,一些研究人员设计了一种刷毛结构非对称的毛刷机器人[14],通过利用刷毛的非对称性,使得毛刷机器人在前后两个方向上的摩擦力大小不一致,从而实现了机器人的单向运动. 在文献[14-16]中,研究者把刷毛简化为扭转弹簧模型,在机器人的竖直方向上安装压电振动器,利用振动器的上下振动,使机器人在上升过程中受到的正压力小于下降时的正压力,从而导致上升时受到的摩擦力小于下降时的,最终实现机器人的单向运动.
迄今为止,大多数关于非对称摩擦的研究仅仅只是简单地利用了该现象,未从力学角度对其进行解释. 同时,非对称摩擦除了与结构本身的非对称性有关外,还与其接触基底的机械性能方面息息相关[12,17]. 因此,本文以具有非对称摩擦现象的钢丝毛刷为研究对象,提出一种基于鬃毛模型和LuGre模型的非对称鬃毛模型,描述钢丝毛刷在正反方向上摩擦力不一致的现象. 以钢丝毛刷的摩擦实验结果为依据,识别非对称鬃毛模型的参数,并从实验和数值模拟角度验证模型的合理性,此外,讨论了该钢丝毛刷在足式机器人领域的应用.
具有非对称摩擦现象的钢丝毛刷如图1所示. 由于钢丝毛刷结构是非对称的,在一定正压力下,正反方向上刷毛与地面间夹角不同,从而引起接触产生的水平分力不同,水平分力即为摩擦力,故钢丝毛刷正反方向摩擦力大小不一致. 为描述钢丝毛刷在正反方向上摩擦力不一致的现象,提出一种非对称鬃毛模型,该模型是基于鬃毛模型和LuGre模型.
鬃毛模型从微观角度描述两个接触表面间接触点的随机行为,将接触看成是大量随机分布的弹性鬃毛间的接触,当接触面产生相对运动时,该模型将滑动体上易弯鬃毛与固定刚性鬃毛间的弹性接触力定义为摩擦力[6]. 本文参照鬃毛模型的建模方式,假定滑动体与固定体之间的接触如图2所示. 图2(a)中,滑动体上分布着多根具有固定初始偏角θ0的鬃毛,固定体上有多个小凸起(假定为尺寸相同的微小长方体),而接触过程则是鬃毛与凸起之间的无摩擦弹性接触且不会触及相邻凸起间的最低处,并假定在给定正压力N的作用下,滑动体与固定体间的垂直距离为h且在接触与分离过程中保持恒定. 图2(b)是单根鬃毛的接触分析,将鬃毛假设为刚度为k的线性扭转弹簧,当单根鬃毛与凸起接触时,鬃毛发生变形且转角为θ,则总转角为θ0+θ,相应扭矩为,在鬃毛与凸起间的接触点存在一个垂直于鬃毛方向的接触力F(不考虑接触点处的摩擦),接触点到鬃毛根部的距离为r.
根据单根鬃毛的受力分析,利用其平衡条件得到=Fr,再结合rh之间的几何关系(r=h/cos(θ+θ0)),可导出单根鬃毛与凸起间的接触力F的水平分力Ff
由式(1)可知摩擦力可由转角θ作为自变量进行描述. 由于存在接触物体之间的相对移动线速度,单根鬃毛与凸起间的接触点的水平速度,可根据几何关系(y=htan(θ+θ0))导出:
由于鬃毛模型存在不连续且计算耗时的缺点,而文献[7]提出的LuGre模型避免了上述问题,其以鬃毛的平均变形量建模,并结合了Dahl模型[2-5]的微分方程描述(将摩擦假设为一种类似弹簧特性的动态行为). 由此,本文除了借鉴鬃毛模型的思想外(将摩擦视为大量随机分布的鬃毛与凸起之间的无摩擦弹性接触),还参考LuGre模型的建立过程,采用鬃毛的平均角度变化量,而非鬃毛模型中大量鬃毛的随机接触,建立非对称鬃毛模型,即:
式(3)中,σ为鬃毛的刚度,为接触物体之间的相对转动角速度,类比式(2)可得到:
式(4)中,为鬃毛固定平均初始偏角,为接触物体之间的相对移动线速度. 此外,式(3)中的函数gω)描述了Stribeck效应[18],其形式可取为:
式(5)中,θsθc类似于静态摩擦系数和动态摩擦系数,ωsc为Stribeck速度.
上述推导是基于正压力不变的假设,而实际情形则是正压力不断发生变化,且摩擦力与正压力成正比. 值得提出的是,在汽车工业领域中有着广泛应用的LuGre轮胎模型[19],其将LuGre模型中摩擦力计算公式当作一个无量纲系数,即摩擦系数. 因此,本文参考LuGre轮胎模型,将式(1)进行无量纲处理得到一个无量纲系数,即摩擦系数,其形式如下:
式(6)中,μ为摩擦系数,N为接触时的正压力.
与LuGre模型建立过程[7]一致,本文考虑到平均角度变化量的阻尼效应,以及当滑动体与固定体之间的相对速度较大时显得尤为突出的粘性效应,参考式(6)得到如下考虑非对称摩擦效应的修正LuGre模型——非对称鬃毛模型:
式(7)中,σ0=k/(Nh)、σ1σ2分别为刚度系数、阻尼系数和黏性摩擦系数,分别对应于鬃毛刚度项、鬃毛阻尼项和黏性摩擦项.
非对称鬃毛模型最终由式(3)、式(4)、式(5)和式(7)描述,且当平均初始偏角时,有如下退化模型:
式(8)中,由于为小量,故,并考虑到角速度与速度均差一比例常数h,式(8)可近似为原始不存在非对称摩擦效应的LuGre模型. 根据文献[20]中LuGre参数辨识的结果可知,σσ1σ2分别为213.75、1.103和0.0005,其中σ1σ2相对于σ0很小,在后续基于实验的参数识别时也能得到类似结论.
为验证钢丝毛刷非对称鬃毛模型的准确性及合理性,本文利用如图3所示的摩擦系数测量实验仪进行试验测量摩擦力并进行参数识别. 摩擦系数测量实验仪由两部分组成:一部分为移动平台,其上可装载接触材料(如铝片等),并用精密直线电机驱动,移动速度可调节;另一部分通过一根弹性绳将力传感器与被测物体(钢丝毛刷)连接,其拉力即为摩擦力. 移动平台尺寸为360 mm*135 mm,力传感器精度为0.02%FS,最大采样频率为60 Hz.
实验所采用的钢丝毛刷,刚毛长度为7.20 mm、刚毛直径为0.10 mm,接触材料为铝片. 为了实验的方便,本文将钢丝毛刷以2*2形式拼接成共有四个钢丝毛刷的组合体(如图4所示),并用夹板固定(钢丝毛刷绕轴不可转动),使其在弹性绳拉伸时不易滑落,且为非滚动接触,钢丝毛刷及其附属结构自重共为212.27 g.
本文分别测量正反方向相对速度从零匀加速到60 mm/s,位移均为300 mm的动态摩擦力随时间变化的曲线,三次典型测量得到的正反方向动态摩擦力Ff随时间t的变化如图5所示. 图5(a)图5(b)中红色、黄色和蓝色实线分别代表三次重复实验结果. 由图5可知,实验可重复性高.
由实验数据可识别非对称鬃毛模型参数. 本文采用最小二乘法识别参数,其中钢丝毛刷的几何参数h均由测量给定,即 rad、h=7.20 mm,其他参数可通过求解如下的优化问题得到:
式(9)中,优化目标J定义为模型对应的摩擦系数数值解μX)与实验值μ之间的二范数,为优化参数,Ф为权重,LbUb分别为参数X的上下限. 基于图5的实验数据最终可识别得到非对称鬃毛模型的参数(如表1所示).
根据表1的优化参数,由非对称鬃毛模型模拟得到的正反方向动态摩擦系数μ随速度v的变化如图8所示. 图6中,蓝色小圆圈和倒三角形分别代表以2*2布局的钢丝毛刷正反方向的实验结果,红色实线和虚线分别代表正反方向参数识别的效果. 由图8可知模拟结果和实验结果相吻合,且非对称鬃毛模型能很好地反映摩擦的方向依赖性.
为进一步验证表1参数识别结果的有效性,本文将钢丝毛刷改为如图7所示以3*3形式拼接成共有六个钢丝毛刷的组合体,钢丝毛刷及其附属结构自重共为300.00 g,且在与上文相同的条件下进行实验. 基于表1的识别参数的非对称鬃毛模型进行模拟得到动态摩擦系数随速度的变化及实验结果如图8所示. 图8中,蓝色小圆圈和倒三角形分别代表以3*3布局的钢丝毛刷正反方向的实验结果,红色实线和虚线分别是非对称鬃毛模型的模拟结果. 从图8可知模拟结果与实验结果吻合,表明参数识别结果的有效性及准确性.
为了研究铝片、尼龙片和陶瓷片等不同接触材料对钢丝毛刷的方向依赖性摩擦的影响,本文采用图4所示2*2形式的钢丝毛刷组合体与三种不同接触材料进行实验,其正反方向动态摩擦系数随速度变化的实验结果如图9所示. 图9中,红色小圆圈、黄色倒三角形、蓝色小四边形分别代表铝、尼龙、陶瓷正反方向的实验结果. 图9表明,钢丝-铝接触对的摩擦方向依赖性最为明显,钢丝-尼龙接触对次之,钢丝-陶瓷接触对相对最小. 由三种接触对的实验数据识别的非对称鬃毛模型的参数如表2所示.
为了验证非对称鬃毛模型的有效性,并讨论该模型对足式机器人的影响,本文采用文献[21]中的四足机器人,将其简化为如图10所示的平面双足机器人.
图10中,平面双足机器人由躯干(蓝色部分)、前腿(绿色实线部分)和后腿(绿色虚线部分)组成,共有7个自由度,分别为躯干平面运动(xy)和俯仰转动θ0以及前后大腿和小腿的关节摆动角度(θ1θ2θ3θ4). 以前腿为例,m0L0I0分别为躯干的质量、长度和转动惯量(若无特殊说明,全文均采用相对质心轴的转动惯量),m1L1l1I1分别为大腿的质量、长度、几何质心位置和转动惯量,m2L2l2I2分别为小腿的质量、长度、几何质心位置和转动惯量,FxfFyf分别为前腿足底水平和竖直方向上的接触力,τhfτkf分别为大腿和小腿电机输出的力矩,前腿动力学模型的典型参数如表3所示,后腿相关参数与前腿一致.
引入平面双足机器人的广义坐标q=[xyθ0θ1θ2θ3θ4]T,则其动力学方程为:
式(10)中,q分别表示机器人广义坐标系及其对应的速度和加速度,Mq)、Gq)分别表示机器人状态相关的惯性矩阵、机器人系统受到的离心力与科里奥利力和每个广义坐标下的重力,g为重力加速度,τa为主动作动力,Jq)为接触雅可比矩阵,F为平面二维接触力. 式(10)中每一项的具体形式见附录公式(1).
基于平面双足机器人的简化动力学模型和非对称鬃毛模型(其参数数值取自表1,法向接触选用Hertz接触模型),本文采用基于直接配点法[22,23]的轨迹优化算法对机器人模型进行一个步态周期内的优化,并考虑耗能小的BB构型[21],其中目标速度设定为vaim=8 m/s,运动轨迹及其相关结果如图11所示.
图11(a)为一个步态周期内的运动轨迹图,红色箭头代表机器人前进方向,实线和虚线分别代表前腿和后腿;图11(b)和图11(c)分别为考虑非对称鬃毛模型和对称模型的方向角(GRF=Fx/Fy)随时间变化图,图中蓝色和红色分别表示前腿和后腿的结果. 图11表明,相比于对称模型,非对称模型能在正方向提供更大的摩擦系数,当在一定正压力下,非对称模型能够在正方向上提供更大的摩擦力,即表明非对称模型能使机器人实现更高的运动速度.
为了更进一步讨论非对称鬃毛模型对足式机器人的影响,本文将轨迹优化的目标速度设定为vaim=20 m/s,研究在不同速度优化目标权重Qv下非对称和对称模型对机器人所能达到最大优化速度umax的影响. 图12中分别讨论了不同权重Qv下非对称鬃毛模型和对称模型所能达到的最大优化速度vmax,其中红色和蓝色曲线分别代表了非对称和对称的结果. 图12表明,非对称模型优化得到的最大优化速度明显优于对称模型,其平均值分别为14.83 m/s、11.58 m/s,非对称模型相比于对称模型提高了28.08%.
为了进一步解释非对称摩擦对足式机器人的影响,本文对平面双足机器人进行理论分析,参考文献[24]可以推导得到足底接触力的理论计算公式:
式(11)中,各物理量的含义与式(10)一致.
本文选取图6所示钢丝毛刷与铝片平稳段的实验结果的平均值作为非对称摩擦的系数,即正反方向稳态摩擦系数为0.9049、0.4314. 作为对比,选取其正反方向稳态摩擦系数的平均值0.6682作为对称摩擦的系数. 通过式(11)进行计算得到接触力并进行归一化,即mtol=m0+m1+m2为总质量,考虑机器人不同姿态的平面xy方向二维接触力结果见图13. 图13中,红色和蓝色有效区间分别为非对称和对称摩擦的结果,图13(a)、图13(b)和图13(c)分别表示躯干俯仰角θ0分别为-5°、0°、5°,且大腿小腿关节角度θ1θ2均为-45°、90°时不同姿态的xy方向接触力结果. 图13显示,非对称摩擦所能提供的最大正向水平接触力明显高于对称摩擦下的结果,且三种不同姿态下分别提高了12.61%、18.79%、17.52%;而竖向最大接触力在不同姿态下基本一致. 由于最大正向水平接触力决定着机器人的加速过程以及能实现的最大速度,故正向水平接触力越大,机器人的加速过程越快,所能实现的最大速度越大,这与图12的轨迹优化结果一致.
从非对称鬃毛模型在足式机器人应用的接触力数值和理论分析可知,非对称鬃毛模型可以得到更大的摩擦力及实现更大的速度.
需要说明的是钢丝毛刷具有非常独特的刚柔耦合结构特性,如将其改装成机器人的蹄子,其非对称鬃毛模型在足式机器人的应用中有一定的潜在优势. 此外,通过实验发现,相比于足式机器人常用的蹄子材料——橡胶,钢丝毛刷具有高摩擦、高耐磨等特性.
本文针对钢丝毛刷表现出的方向依赖性摩擦现象,结合鬃毛模型和LuGre模型思想,提出了非对称鬃毛模型,同时利用不同构型钢丝毛刷组合体的实验得到正反方向上的速度-动态摩擦系数关系曲线,并通过最小二乘法识别得到模型的参数,数值模拟和实验结果验证钢丝毛刷的非对称鬃毛模型有效性和准确性. 然后通过建立平面双足机器人简化模型,并结合非对称鬃毛模型建立系统的动力学方程,利用实验识别得到非对称鬃毛模型的参数数值进行轨迹优化,发现非对称模型能提高接触时的正向摩擦系数,进而提高足式机器人最大运动速度理论分析进一步说明非对称模型的优势.
此外,钢丝毛刷具有非常独特的刚柔结构,实验结果表明相比于常用的蹄子材料——橡胶其具有高摩擦、高耐磨等优势. 因此钢丝毛刷所具有的这些特性在足式机器人领域将有潜在的实际应用前景.
公式(1)
公式(1)中,为了简化表达式,本文将部分表达式用符号进行替换,具体形式见下式,且其他若如无特殊说明均遵从这一约定。
  • 国家自然科学基金项目(12132013)
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2024年第45卷第4期
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doi: 10.19636/j.cnki.cjsm42-1250/o3.2024.014
  • 接收时间:2024-03-14
  • 首发时间:2026-04-01
  • 出版时间:2024-08-25
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  • 收稿日期:2024-03-14
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国家自然科学基金项目(12132013)
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    浙江大学航空航天学院,杭州,310000

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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