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Morphological Intelligence Mechanisms in Biological and Biomimetic Flow Sensing

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机构: [1]Beihang Univ, Sch Mech Engn & Automat, Inst Bion & Micronano Syst, Beijing 100191, Peoples R China [2]Capital Med Univ, Beijing Tongren Hosp, Beijing Tongren Eye Ctr, Beijing Ophthalmol & Visual Sci Key Lab, Beijing 100069, Peoples R China
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关键词: biomechanical filters biomimetic sensors flow sensing morphological intelligence nonlinear mechanics

摘要:
Many aquatic and aerial animals have evolved highly sensitive flow receptors to help them survive in challenging environments. The biological flow receptors, such as filiform hairs, lateral lines, and seal whiskers, are elegantly designed with interesting biomechanical processing principles for extreme sensitivity, exhibiting obvious morphological intelligence. For instance, superficial neuromasts on the surface of fish body have an elongated cupula to enhance flow detection with a magnified drag. The flow-induced mechanical information is transferred to arrayed hair bundles in the neuromasts, which show spontaneous oscillation and mechanical coupling effects for a high mechanical sensitivity. In this review, the biomechanical principles of morphological intelligence in biological flow field receptors are discussed, with an emphasis on the functions of stimulus enhancement, noise reduction, and nonlinear oscillation. In addition, the recent achievements in flow sensors with morphological intelligence are summarized in this article. Though there is still a big gap in principle discovery and practical application of morphological intelligence in engineered sensors, it can be anticipated that the field of intelligent flow sensing will be significantly promoted by the establishment of morphological intelligence models.

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基金编号: 52022008 51975030 T2121003

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出版当年[2022]版:
大类 | 3 区 计算机科学
小类 | 3 区 计算机:人工智能 3 区 自动化与控制系统 3 区 机器人学
最新[2025]版:
大类 | 3 区 计算机科学
小类 | 3 区 自动化与控制系统 3 区 计算机:人工智能 3 区 机器人学
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出版当年[2021]版:
Q1 AUTOMATION & CONTROL SYSTEMS Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Q1 ROBOTICS
最新[2023]版:
Q1 AUTOMATION & CONTROL SYSTEMS Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Q1 ROBOTICS

影响因子: 最新[2023版] 最新五年平均 出版当年[2021版] 出版当年五年平均 出版前一年[2020版] 出版后一年[2022版]

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第一作者机构: [1]Beihang Univ, Sch Mech Engn & Automat, Inst Bion & Micronano Syst, Beijing 100191, Peoples R China
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