Tactile perception of randomly rough surfaces

相似性(几何) 人工智能 表面粗糙度 比例(比率) 算法 材料科学 计算机科学 数学 几何学 物理 图像(数学) 复合材料 量子力学
作者
Riad Sahli,Aubin JC. M. Prot,Anle Wang,Martin H. Müser,Michal Piovarči,Piotr Didyk,Roland Bennewitz
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:10 (1): 15800-15800 被引量:41
标识
DOI:10.1038/s41598-020-72890-y
摘要

Most everyday surfaces are randomly rough and self-similar on sufficiently small scales. We investigated the tactile perception of randomly rough surfaces using 3D-printed samples, where the topographic structure and the statistical properties of scale-dependent roughness were varied independently. We found that the tactile perception of similarity between surfaces was dominated by the statistical micro-scale roughness rather than by their topographic resemblance. Participants were able to notice differences in the Hurst roughness exponent of 0.2, or a difference in surface curvature of 0.8 [Formula: see text] for surfaces with curvatures between 1 and 3 [Formula: see text]. In contrast, visual perception of similarity between color-coded images of the surface height was dominated by their topographic resemblance. We conclude that vibration cues from roughness at the length scale of the finger ridge distance distract the participants from including the topography into the judgement of similarity. The interaction between surface asperities and fingertip skin led to higher friction for higher micro-scale roughness. Individual friction data allowed us to construct a psychometric curve which relates similarity decisions to differences in friction. Participants noticed differences in the friction coefficient as small as 0.035 for samples with friction coefficients between 0.34 and 0.45.
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
Captain_H发布了新的文献求助10
刚刚
花开富贵发布了新的文献求助10
1秒前
訾化端发布了新的文献求助10
2秒前
3秒前
细腻傲柔完成签到,获得积分10
4秒前
AntonioJ完成签到,获得积分10
5秒前
niting123456完成签到,获得积分10
5秒前
我谈发布了新的文献求助10
6秒前
7秒前
7秒前
7秒前
9秒前
9秒前
12秒前
訾化端完成签到,获得积分10
12秒前
fahui发布了新的文献求助10
13秒前
14秒前
14秒前
kangkang发布了新的文献求助10
14秒前
Captain_H完成签到,获得积分10
15秒前
15秒前
17秒前
大大撒发布了新的文献求助10
18秒前
18秒前
欣慰雪巧完成签到 ,获得积分10
19秒前
20秒前
20秒前
epiphany完成签到,获得积分10
20秒前
times发布了新的文献求助20
21秒前
笑点低的危完成签到,获得积分10
21秒前
Busy完成签到 ,获得积分10
22秒前
科研通AI6.4应助ccc采纳,获得10
22秒前
22秒前
22秒前
22秒前
彭于晏应助JohniferCheong采纳,获得10
23秒前
evak发布了新的文献求助10
24秒前
医只兔发布了新的文献求助20
24秒前
24秒前
kangkang完成签到,获得积分10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Governing Growth: Us Industrial Policy from Hamilton to Trump 500
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
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 7625477
求助须知:如何正确求助?哪些是违规求助? 9200440
关于积分的说明 19726015
捐赠科研通 7196470
什么是DOI,文献DOI怎么找? 3273697
关于科研通互助平台的介绍 2435853
邀请新用户注册赠送积分活动 2269553