Underwater Bionic Tactile Sensing: Biological Perception Mechanisms, Technological Progress, and Future Challenges

水下 仿生学 计算机科学 感知 工程类 触觉知觉 人工智能 计算机视觉 人机交互 仿生学 感觉系统 侧线 海洋工程 触觉传感器 声学 水母
作者
Xinyue Zhou,Yuanzheng Li,Jianhua Liu,Xingfu Wan,Gengchen Xu,Aiqiang Yu,Z.M. Su,Bowen Dong,Kecheng Zhang,Fanqing Hu,Yuchen Li,Xinlei Liu,Peng Xu,Siyuan Wang,Minyi Xu
出处
期刊:Advanced materials and technologies [Wiley]
卷期号:11 (8)
标识
DOI:10.1002/admt.202502446
摘要

ABSTRACT Marine organisms are known to rely on highly sensitive tactile organs to accurately perceive external disturbances, particularly in low‐light or completely dark underwater environments. These tactile perceptual mechanisms serve as ideal biological prototypes for the development of advanced underwater sensing devices. This manuscript provides a comprehensive review of the perceptual mechanisms of marine organisms and their technological translations. The intricate sensory systems of three representative species are examined: the lateral line system of fish, featuring both superficial and canal neuromasts for precise fluid dynamic detection; the undulating morphology of seal whiskers, specialized for hydrodynamic trail tracking; and the highly flexible tentacles of certain marine organisms, capable of detecting underwater pressure and deformation with exceptional sensitivity. Inspired by these biological mechanisms, biomimetic tactile sensors have been developed based on triboelectric, piezoelectric, piezoresistive, capacitive, magnetic, and optical fiber principles. Their broad application potential has been highlighted in tasks such as underwater flow velocity monitoring, vortex detection, and underwater object manipulation. Finally, current challenges, including environmental interference and limited durability, are discussed, along with future directions such as multimodal sensing integration and AI‐assisted data processing, providing valuable insights for advancing next‐generation underwater tactile sensing technologies.
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
東染发布了新的文献求助10
刚刚
完美世界应助夏梓硕采纳,获得10
刚刚
youlingmaomao关注了科研通微信公众号
刚刚
时尚的雯完成签到 ,获得积分10
1秒前
Ava应助111采纳,获得10
1秒前
VV发布了新的文献求助10
1秒前
六万发布了新的文献求助30
1秒前
2秒前
瀚的喵发布了新的文献求助30
2秒前
qinchuanniu发布了新的文献求助10
3秒前
qugo完成签到,获得积分10
3秒前
萌大完成签到 ,获得积分20
3秒前
3秒前
Owen应助科研通管家采纳,获得10
3秒前
3秒前
赘婿应助huhu采纳,获得10
3秒前
充电宝应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
搜集达人应助科研通管家采纳,获得10
3秒前
Farson应助科研通管家采纳,获得10
4秒前
科研通AI6.2应助科研通管家采纳,获得100
4秒前
研友_VZG7GZ应助科研通管家采纳,获得10
4秒前
4秒前
charint应助科研通管家采纳,获得20
4秒前
不知道发布了新的文献求助10
4秒前
李健应助科研通管家采纳,获得10
4秒前
今后应助科研通管家采纳,获得10
4秒前
科研通AI6.4应助Dr_Fight采纳,获得30
4秒前
4秒前
脑洞疼应助科研通管家采纳,获得10
4秒前
酷波er应助科研通管家采纳,获得10
4秒前
4秒前
汉堡包应助科研通管家采纳,获得10
5秒前
Orange应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
qiting0519完成签到,获得积分10
5秒前
SciGPT应助科研通管家采纳,获得10
5秒前
arniu2008应助科研通管家采纳,获得20
5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
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
日本現代怪異事典 副読本 700
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 650
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
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 7395759
求助须知:如何正确求助?哪些是违规求助? 9001748
关于积分的说明 19159796
捐赠科研通 7031418
什么是DOI,文献DOI怎么找? 3229941
关于科研通互助平台的介绍 2392359
邀请新用户注册赠送积分活动 2211545