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首页> 外文期刊>The Journal of Experimental Biology >Individual variation and the biomechanics of maneuvering flight in hummingbirds
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Individual variation and the biomechanics of maneuvering flight in hummingbirds

机译:蜂鸟的单个变异和机动飞行的生物力学

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摘要

An animal s maneuverability will determine the outcome of many of its most important interactions. A common approach to studying maneuverability is to force the animal to perform a specific maneuver or to try to elicit maximal performance. Recently, the availability of wider-field tracking technology has allowed for high-throughput measurements of voluntary behavior, an approach that produces large volumes of data. Here, we show how these data allow for measures of inter-individual variation that are necessary to evaluate how performance depends on other traits, both within and among species. We use simulated data to illustrate best practices when sampling a large number of voluntary maneuvers. Our results show how the sample average can be the best measure of interindividual variation, whereas the sample maximum is neither repeatable nor a useful metric of the true variation among individuals. Our studies with flying hummingbirds reveal that their maneuvers fall into three major categories: simple translations, simple rotations and complex turns. Simple maneuvers are largely govemed by distinct morphological and/or physiological traits. Complex turns involve both translations and rotations, and are more subject to inter-individual differences that are not explained by morphology. This three-part framework suggests that different wingbeat kinematics can be used to maximize specific aspects of maneuverability. Thus, a broad explanatory framework has emerged for interpreting hummingbird maneuverability. This framework is general enough to be applied to other types of locomotion, and informative enough to explain mechanisms of maneuverability that could be applied to both animals and bio-inspired robots.
机译:动物的机动性将确定许多最重要的相互作用的结果。学习机动性的常见方法是迫使动物进行特定的机动或尝试引出最大性能。最近,更广泛现场跟踪技术的可用性允许对自愿行为的高吞吐量测量,一种产生大量数据的方法。在这里,我们展示这些数据如何允许各种各种变化的措施来评估性能如何取决于物种内部和之间的其他特征。我们使用模拟数据来说明在抽样大量自愿操纵时说明最佳实践。我们的结果表明,样本平均值如何是互动变化的最佳衡量标准,而样本最大既不是可重复的,也不是个体之间真正变异的有用度量。我们与飞行蜂鸟的研究表明,他们的演习分为三大类:简单的翻译,简单的旋转和复杂的转弯。简单的演习主要通过不同的形态和/或生理性状来统治。复杂的转弯涉及翻译和旋转,并且更受形态未解释的单独差异。这三部分框架表明,可以使用不同的翼展运动学来最大限度地提高机动性的特定方面。因此,出现了一种广泛的解释蜂窝机动性的解释性框架。该框架足以适用于其他类型的运动,并且提供足够的信息,以解释可以应用于动物和生物启发机器人的机动性的机制。

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