MRI: Acquisition of a High Resolution High Speed 3D Motion Tracking System for Multi-Disciplinary Research and Research Training
MRI:获取高分辨率高速 3D 运动跟踪系统,用于多学科研究和研究培训
基本信息
- 批准号:1827495
- 负责人:
- 金额:$ 27.24万
- 依托单位:
- 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
- 起止时间:2018-10-01 至 2021-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This Major Research Instrumentation (MRI) award supports the acquisition of a versatile high speed, high precision 3D motion tracking system to enable fundamental research and education in biomechanics, dynamics and controls, robotics, neuroscience and biology. Greater understanding of animal motions and communication will enable design of robots with more versatile movement patterns and that can be more effective partners with humans in activities ranging from disaster recovery to health care and manufacturing. It will also provide the basis for new treatments for joint injuries and strategies to mitigate damage from osteoarthritis. This 3D motion capture system will be the centerpiece of a common space in which student and faculty researchers can engage in interdisciplinary collaborations. The acquisition will integrate high speed high precision motion tracking techniques into undergraduate STEM research and teaching, along with new tools, methods, and environments to foster the development of future researchers. Targeted programs at the university will enhance the participation of underrepresented groups. The 3D motion capture system is built around 20 Oqus 7+ cameras, each capable of a sustained data rate of 3.6 Gigapixels/sec -- allowing for frame rates and resolutions ranging from 12 Megapixels at 300fps to 3 Megapixels at 1100fps. The high-resolution and high-speed motion is needed to capture animals' complex, fast, and often subtle motion patterns for a better understanding of how body size affects locomotion, how injuries affect gait, and the role of motion in social interactions. The instrumentation can be configured into different size arenas to investigate a wide variety of issues, ranging from how soft systems learn to leverage their material properties to produce fast, dynamic and resilient behaviors (large set up) to smaller capture arenas with tracking of dozens of 1mm markers at sub-millimeter resolution to understand the complex relationship between joint loading and structural changes in bone.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.
该重大研究仪器(MRI)奖支持收购多功能高速,高精度3D运动跟踪系统,以实现生物力学,动力学和控制,机器人,神经科学和生物学的基础研究和教育。对动物运动和交流的更深入了解将使机器人的设计具有更灵活的运动模式,并且可以在从灾难恢复到医疗保健和制造业的活动中与人类进行更有效的合作。 它还将为关节损伤的新治疗方法和减轻骨关节炎损害的策略提供基础。这个3D运动捕捉系统将成为一个共同空间的核心,在这个空间中,学生和教师研究人员可以进行跨学科的合作。此次收购将把高速高精度运动跟踪技术整合到本科STEM研究和教学中,沿着新的工具、方法和环境,以促进未来研究人员的发展。在大学有针对性的方案将提高代表性不足的群体的参与。3D动作捕捉系统围绕20个Oqus 7+摄像头构建,每个摄像头的持续数据速率为3.6千兆像素/秒-允许帧速率和分辨率从300 fps的1200万像素到1100 fps的300万像素。需要高分辨率和高速运动来捕捉动物复杂,快速且通常微妙的运动模式,以便更好地了解身体大小如何影响运动,受伤如何影响步态以及运动在社会互动中的作用。仪器可以配置成不同大小的舞台,以研究各种各样的问题,从软系统如何学习利用其材料特性来快速生产,动态和弹性行为(大型设置)到较小的捕获竞技场,跟踪数十个1 mm标记,毫米分辨率,以了解关节负荷和骨结构变化之间的复杂关系。该奖项反映了NSF的法定使命,通过使用基金会的知识价值和更广泛的影响审查标准进行评估,认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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John Rieffel其他文献
Trent McConaghy, P. Palmers, G. Peng, Michiel Steyaert, Georges Gielen: Variation-aware analog structural synthesis: a computational intelligence approach
- DOI:
10.1007/s10710-011-9145-2 - 发表时间:
2011-08-07 - 期刊:
- 影响因子:0.900
- 作者:
John Rieffel - 通讯作者:
John Rieffel
EvoFab: A Fully Embodied Evolutionary Fabricator
EvoFab:完全体现的进化制造商
- DOI:
- 发表时间:
2010 - 期刊:
- 影响因子:0
- 作者:
John Rieffel;D. Sayles - 通讯作者:
D. Sayles
Robustness for Free: Quality-Diversity Driven Discovery of Agile Soft Robotic Gaits
免费的鲁棒性:质量多样性驱动的敏捷软机器人步态的发现
- DOI:
10.48550/arxiv.2311.01245 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
John Daly;Daniel Casper;Muhammad Farooq;Andrew James;Ali Khan;Phoenix Mulgrew;Daniel Tyebkhan;Bao Vo;John Rieffel - 通讯作者:
John Rieffel
Robustness in Diversity: Quality-Diversity Driven Discovery of Agile Soft Robotic Gaits
多样性的鲁棒性:质量多样性驱动的敏捷软机器人步态的发现
- DOI:
10.1109/robosoft60065.2024.10521943 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
John Daly;Daniel Casper;Muhammad Farooq;Andrew James;Ali Khan;Phoenix Mulgrew;Daniel Tyebkhan;Bao Vo;John Rieffel - 通讯作者:
John Rieffel
John Rieffel的其他文献
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{{ truncateString('John Rieffel', 18)}}的其他基金
EAGER: Behavioral Repertoires for Soft Robotics
EAGER:软机器人的行为库
- 批准号:
1939930 - 财政年份:2019
- 资助金额:
$ 27.24万 - 项目类别:
Standard Grant
MRI: Acquisition of a Multi-Material 3D Printer to Enable Novel Multi-disciplinary Research and Research Training
MRI:购买多材料 3D 打印机以实现新颖的多学科研究和研究培训
- 批准号:
1337768 - 财政年份:2013
- 资助金额:
$ 27.24万 - 项目类别:
Standard Grant
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