Characterization of Wing Kinematics by Decoupling Joint Movement in the Pigeon.

IF 3.4 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY Biomimetics Pub Date : 2024-09-15 DOI:10.3390/biomimetics9090555
Yishi Shen, Shi Zhang, Weimin Huang, Chengrui Shang, Tao Sun, Qing Shi
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Abstract

Birds have remarkable flight capabilities due to their adaptive wing morphology. However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To address this issue and provide a complete dataset, we recorded comprehensive motion capture wing trajectory data from five free-flying pigeons (Columba livia). Five key motion parameters are used to quantitatively characterize wing kinematics: flapping, sweeping, twisting, folding and bending. In addition, the forelimb skeleton is mapped using an open-chain three-bar mechanism model. By systematically evaluating the relationship of joint degrees of freedom (DOFs), we configured the model as a 3-DOF shoulder, 1-DOF elbow and 2-DOF wrist. Based on the correlation analysis between wingbeat kinematics and joint movement, we found that the strongly correlated shoulder and wrist roll within the stroke plane cause wing flap and bending. There is also a strong correlation between shoulder, elbow and wrist yaw out of the stroke plane, which causes wing sweep and fold. By simplifying the wing morphing, we developed three flapping wing robots, each with different DOFs inside and outside the stroke plane. This study provides insight into the design of flapping wing robots capable of mimicking the 3D wing motion of pigeons.

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通过解耦鸽子的关节运动来确定翅膀运动学的特征。
鸟类因其适应性翅膀形态而具有非凡的飞行能力。然而,研究活体鸟类费时费力,而且很难获得完整的拍翅周期信息。为了解决这个问题并提供一个完整的数据集,我们记录了五只自由飞行的鸽子(Columba livia)的全面运动捕捉翅膀轨迹数据。五个关键运动参数用于定量描述翅膀运动学特征:拍打、横扫、扭转、折叠和弯曲。此外,还利用开链三杆机构模型绘制了前肢骨骼图。通过系统评估关节自由度(DOF)的关系,我们将模型配置为 3-DOF 肩部、1-DOF 肘部和 2-DOF 腕部。根据翼搏运动学与关节运动之间的相关性分析,我们发现肩部和腕部在冲程平面内的滚动与翼搏运动学之间存在强烈的相关性,会导致机翼翻转和弯曲。在冲程平面外,肩、肘和腕偏航之间也有很强的相关性,这导致了机翼的横扫和折叠。通过简化机翼变形,我们开发了三种拍翼机器人,每种机器人在冲程平面内外都有不同的 DOF。这项研究为设计能够模仿鸽子三维翅膀运动的拍翼机器人提供了启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
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