NRI: FND: COLLAB: A Foundational Approach to Muscle Actuators that Lowers Barriers to Muscle-Powered Robotics Research

NRI：FND：COLLAB：肌肉驱动器的基础方法，降低肌肉动力机器人研究的障碍

• 批准号: 1830291
• 负责人: Robert Wood
• 金额: $ 36.08万
• 依托单位: Harvard University
• 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: 2018-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830291&HistoricalAwards=false
• 关键词: NRI; FND; COLLAB; Foundational; Approach

This National Robotics Initiative (NRI) project will promote the progress of science and advance the national prosperity by developing a foundational approach towards muscle-powered machines that move using biomimetic muscle actuators. Biomimetic muscle actuators, or robot muscles, are actuators that closely mimic the properties of biological muscles in nature. A common set of challenges in actuator selection and design, and modeling and controlling behaviors and properties emerge among different muscle actuators. This award supports identifying and unifying modeling, control, and design strategies that would lower the barrier to muscle-powered robotics research. A significant effort to de-risk robot muscles for designers is the creation of a robot muscles toolkit, an accessible software and hardware toolkit for designing muscle-powered machines and for democratizing the development and proliferation of these technologies at a broad scale. Design challenges and competitions will spur the interests and community building for those interested in robot muscles across all ages and experiences, from K-12 to college students and researchers. Local arrangements for outreach in the San Diego and Greater Boston Area communities are planned for stirring interest in robotics for underrepresented minorities.A novel, data-driven process and structure for parameterizing a common set of biomimetic features that define muscle actuation will be developed in order to anchor modeling, control, and design strategies across a so-called performance and configuration space. These methods can be employed across muscle types and generalize beyond currently available muscle actuators. There is a strategy for muscle selection over multi-dimensional performance criteria that incorporates both empirical data and physics models. Design strategies for muscle configurations for amplification along these performance dimensions, generalizable across muscles, will be investigated. New technologies will be able to be easily added into this framework to perform quantitative comparison studies without replication of gold standard actuators.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.

这项国家机器人倡议（NRI）项目将通过为使用仿生肌肉执行器移动的肌肉动力机器开发基础方法来促进科学的进步，并促进国家繁荣。仿生肌肉致动剂或机器人肌肉是致动子，它们在自然界中密切模仿生物肌肉的特性。执行器选择和设计中的一组挑战，以及在不同的肌肉执行器中出现的建模和控制行为和特性。该奖项支持识别和统一建模，控制和设计策略，以降低肌肉动力机器人研究的障碍。 为设计师脱离风险的机器人肌肉的一项巨大努力是创建机器人肌肉工具包，可访问的软件和硬件工具包，用于设计肌肉动力的机器，并在广泛规模上使这些技术的开发和增殖民主化。设计挑战和比赛将激发人们对从K-12到大学生和研究人员的所有年龄和经验感兴趣的人感兴趣的人的兴趣和社区建设。 计划在圣地亚哥和大波士顿地区社区进行宣传的地方安排，以激发人们对代表性不足的少数群体的兴趣。一种新颖的，数据驱动的过程和结构，用于参数化一组常见的生物可能性特征，以定义定义肌肉驱动的共同特征在所谓的性能和配置空间中锚定建模，控制和设计策略。这些方法可以在肌肉类型中采用，并推广到当前可用的肌肉执行器之外。对于多维性能标准，有一种肌肉选择的策略，该策略既包含经验数据和物理模型。将研究沿着这些性能维度扩增的肌肉配置的设计策略，可在整个肌肉之间进行概括。新技术将能够轻松地添加到该框架中，以进行定量比较研究，而无需复制黄金标准执行器。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子和更广泛影响的评估标准来通过评估来获得支持的。

项目成果

Robotic Artificial Muscles: Current Progress and Future Perspectives

• DOI: 10.1109/tro.2019.2894371
• 发表时间: 2019-06-01
• 期刊: IEEE TRANSACTIONS ON ROBOTICS
• 影响因子: 7.8
• 作者: Zhang, Jun;Sheng, Jun;Yip, Michael C.
• 通讯作者: Yip, Michael C.

Controlled flight of a microrobot powered by soft artificial muscles

• DOI: 10.1038/s41586-019-1737-7
• 发表时间: 2019-11-14
• 期刊: NATURE
• 影响因子: 64.8
• 作者: Chen, Yufeng;Zhao, Huichan;Wood, Robert J.
• 通讯作者: Wood, Robert J.

A dynamic electrically driven soft valve for control of soft hydraulic actuators

• DOI: 10.1073/pnas.2103198118
• 发表时间: 2021-08
• 期刊: Proceedings of the National Academy of Sciences
• 作者: Siyi Xu;Yufeng Chen;N. P. Hyun;Kaitlyn P. Becker;R. Wood

Microrobotic laser steering for minimally invasive surgery

• DOI: 10.1126/scirobotics.abd5476
• 发表时间: 2021-01
• 期刊: Science Robotics
• 影响因子: 25
• 作者: Peter A. York;Rut Peña;D. Kent;R. Wood