MRI: Development of a System for High-Resolution Uninterrupted Capture of Complex Animal Motions
MRI: Development of a System for High-Resolution Uninterrupted Capture of Complex Animal Motions
批准号:
1828280
负责人:
Rolf Mueller
金额:
$24.97万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2022-09-30
中文摘要
这一重大研究仪器奖支持开发一种集成的相机阵列,该阵列将进行定制,以应对捕捉快速和高度复杂的动物运动的挑战--为基础研究提供一个理解运动动力学并对其建模的使能工具。该仪器将允许对动物身上数百个点进行不间断的运动跟踪,因为它甚至可以执行最复杂的运动,例如蝙蝠在空中追逐猎物时的空中翻筋斗。将产生的数据的前所未有的细节、质量和数量将为新的基础研究提供基础,以了解动物如何利用行动自由在机动性和能效方面获得无与伦比的表现水平。该仪器产生的大量定量数据将使数据密集型方法--从非线性动力学和机器学习--应用于动物运动领域。更深入地理解动物运动背后的原理将是开发能够处理不受限制的自然环境的下一代移动机器人的关键。这些高度灵巧的移动机器人将提高制造业、医疗保健、灾难应对、精准农业、林业以及环境监测和清理等应用的生产率。该仪器还将能够对人造结构的运动进行基础研究,例如气动系统中颤振固有的复杂动态运动。从这台仪器收集到的知识也将帮助兽医从动物的运动模式中诊断疾病和疼痛。研究生和本科生将参与仪器设备的开发,仪器设备将提供工程和生物方面的跨学科研究培训机会。该仪器将把高空间和时间分辨率与同时从多个不同角度观察运动动物的能力结合在一起。它将由48个高速摄像机组成,可以在1057-Hz的帧速率下提供1280x1024像素的图像分辨率。高质量的照明将由8个特殊的灯光提供,这样动物运动的任何部分都不会被隐藏在视线之外。阵列中的所有摄像头都将同步(精度为10纳秒)并自动操作,以便高效地捕获大型运动数据集。例如,5秒的记录将产生超过250,000张图像和332 GB的原始数据。该项目团队的自动图像处理方法将允许在如此大的图像集中可靠地跟踪数百个地标点。该仪器及其配套的软件工具套件将用于研究以前未解释的动物运动能力,如高度铰接的蝙蝠飞行、蛇的滑翔和在垂直基质上奔跑的蜥蜴。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This major research instrumentation award supports the development of an integrated camera array that will be customized to meet the challenges of capturing fast and highly complex animal motions--providing an enabling tool for fundamental research to understand and model the dynamics of motion. The instrument will permit uninterrupted motion tracking for hundreds of points on an animal as it executes even the most complex motions, such as midair somersaults that bats perform in pursuit of prey. The unprecedented detail, quality, and quantity of the data to be generated will provide the basis for new fundamental research into how animals use freedom of movement to attain unmatched levels of performance in maneuverability and energy efficiency. The large volume of quantitative data produced by the instrument will bring data-intensive methods--from non-linear dynamics and machine learning-- to bear on the field of animal motion. A deeper understanding of the principles behind animal motion will be key to the development of next-generation mobile robots that can handle unconstrained, natural environments. These highly dexterous, mobile robots will enhance productivity in applications such as manufacturing, health care, disaster response, precision agriculture, forestry and environmental monitoring and clean-up. This instrument will also enable fundamental research on the motion of man-made structures, such as the complex dynamic motions inherent in flutter in aerodynamic systems. Knowledge gleaned from this instrument will also help veterinarians to diagnose disease and pain from animals' motion patterns. Graduate and undergraduate students will be involved in instrumentation development and the instrumentation will enable interdisciplinary research training opportunities in engineering and biology. The instrument will combine high spatial and temporal resolution with the ability to view a moving animal from many different angles at the same time. It will consist of 48 high-speed video cameras that can deliver a 1280x1024-pixel image resolution at 1057-Hz frame rate. High-quality illumination will be provided by 8 specialized lights so that no part of a moving animal will ever be hidden from view. All cameras in the array will be synchronized (precision 10 nanoseconds) and operated automatically to allow for efficient capture of large motion data sets. A recording of 5 seconds, for example, will result in over 250,000 images with 332 Gigabytes of raw data. The project team's automated image processing methods will allow reliable tracking of several hundred landmark points across such large image sets. The instrument and its accompanying suite of software tools will be used for the study of previously unexplained animal motion capabilities such as the highly articulated flight of bats, gliding of snakes, and lizards running on vertical substrates.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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A Perturbation Method For the Tomographic Reconstruction of Acoustic Images
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