EFRI C3 SoRo: Functional-Domain Soft Robots Precisely Controlled by Quantitative Dynamic Models and Data

EFRI C3 SoRo：由定量动态模型和数据精确控制的功能域软机器人

• 批准号: 1935291
• 负责人: Xuanhe Zhao
• 金额: $ 200万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935291&HistoricalAwards=false
• 关键词: EFRI; C3; SoRo; Functional; Domain

This project will create a new class of submillimeter surgical soft robots, capable of untethered operation in the human body, and enabled by programmable domains of soft functional materials designed to respond in different ways to external magnetic fields. These materials can be used to propel and steer the robot or to trigger permanent shape change, with different functions selected by the frequency of the forcing field. Other material domains are designed to provide distributed sensing through changes in electronic properties. At the system level, both model-based and data-driven methods will be used to modulate the external magnetic field to control the robot in the body, based on real-time fluoroscopy images and information from the robot's sensors. Robot performance will be experimentally validated, including in animal models. The result will be enhanced accuracy, steerability, and navigability over conventional techniques, thus providing access to complex and constrained environments unreachable by existing surgical robots or robotic catheters. These new robots will open new venues for minimally invasive surgery and potentially address longstanding challenges and unmet needs in healthcare. The project will be carried out by a team of researchers with complementary expertise, including soft active materials design and fabrication, constitutive modeling and mechanics, flexible electronics and sensors, machine learning and data processing, medical device design, and translational medicine. The project will provide research and training opportunities to graduate, undergraduate and high school students from underrepresented groups, and will offer workshops and seminars for K-12 students.Soft robots are currently facing a set of key challenges including untethered actuation, distributed sensing, accurate control, and miniaturization. This project seeks to address the challenges through a paradigm-shifting functional-domain approach for the design, fabrication, and control of a new class of functional-domain soft robots (FunDo SoRo). FunDo SoRo with self-contained multi-functional domains of programmable actuation and distributed sensing and data-driven strategies for accurate dynamics control will represent a new paradigm in the design, manufacture and control of soft robotics. The specific approaches in achieving FunDo SoRo are to 1) develop novel functional materials and multi-material 3D printing techniques to realize field-based remote actuation, shape-reconfiguration, and distributed sensing through a set of integrated actuation domains responsive to static magnetic fields, shape-memory domains reconfigurable under dynamic magnetic fields, and sensing domains capable of measuring strain, contact pressure, and temperature; 2) develop theoretical and computational models to quantitatively predict the dynamic response of FunDo SoRo upon actuation, and data-driven strategies assisted by machine learning to accurately control the dynamics of FunDo SoRo; and 3) experimentally validate submillimeter soft continuum robots for minimally invasive procedures to address unmet needs and challenges in healthcare such as cerebral aneurysms or obstructive pulmonary diseases.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.

该项目将创建一种新型的亚毫米外科软机器人，能够在人体内进行不受约束的操作，并通过设计用于以不同方式响应外部磁场的软功能材料的可编程域来实现。这些材料可用于推进和操纵机器人或触发永久形状变化，并通过强制场的频率选择不同的功能。其他材料域被设计成通过电子特性的变化来提供分布式感测。在系统层面，基于模型和数据驱动的方法将用于调制外部磁场，以根据实时荧光透视图像和机器人传感器的信息控制体内的机器人。机器人性能将通过实验验证，包括在动物模型中。其结果将是增强的准确性，可操纵性和导航性超过传统技术，从而提供访问复杂和限制的环境无法达到现有的手术机器人或机器人导管。这些新机器人将为微创手术开辟新的场所，并有可能解决医疗保健领域长期存在的挑战和未满足的需求。该项目将由一组具有互补专业知识的研究人员进行，包括软活性材料设计和制造，本构建模和力学，柔性电子和传感器，机器学习和数据处理，医疗设备设计和转化医学。该项目将为来自代表性不足群体的研究生、本科生和高中生提供研究和培训机会，并将为K-12学生提供讲习班和研讨会。软机器人目前面临着一系列关键挑战，包括无绳驱动、分布式传感、精确控制和小型化。该项目旨在通过一种范式转换的功能域方法来解决这些挑战，用于设计，制造和控制一类新的功能域软机器人（FunDo索罗）。FunDo索罗具有可编程驱动和分布式传感的独立多功能域以及用于精确动态控制的数据驱动策略，将代表软机器人设计，制造和控制的新范式。实现FunDo索罗的具体途径是：1）开发新型功能材料和多材料3D打印技术，通过一组响应于静态磁场的集成致动域、动态磁场下可重构的形状记忆域和能够测量应变、接触压力和温度的传感域，实现基于场的远程致动、形状重构和分布式传感; 2）开发理论和计算模型，以定量预测FunDo索罗在驱动时的动态响应，以及由机器学习辅助的数据驱动策略，以准确控制FunDo索罗的动态;和3）实验验证亚毫米软连续体机器人用于微创手术，以解决脑动脉瘤或阻塞性肺病等医疗保健领域未满足的需求和挑战。NSF的法定使命，并已被认为是值得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的支持。

项目成果

Magnetic Soft Materials and Robots.

• DOI: 10.1021/acs.chemrev.1c00481
• 发表时间: 2022-03-09
• 期刊: CHEMICAL REVIEWS
• 影响因子: 62.1
• 作者: Kim, Yoonho;Zhao, Xuanhe
• 通讯作者: Zhao, Xuanhe

A Multifunctional Origami Patch for Minimally Invasive Tissue Sealing.

• DOI: 10.1002/adma.202007667
• 发表时间: 2021-03
• 期刊: Advanced materials (Deerfield Beach, Fla.)
• 作者: Wu SJ;Yuk H;Wu J;Nabzdyk CS;Zhao X
• 通讯作者: Zhao X

Telerobotic neurovascular interventions with magnetic manipulation.

• DOI: 10.1126/scirobotics.abg9907
• 发表时间: 2022-04-13
• 期刊: Science robotics
• 影响因子: 25

Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity.

• DOI: 10.1038/s41467-021-23802-9
• 发表时间: 2021-06-08
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Park S;Yuk H;Zhao R;Yim YS;Woldeghebriel EW;Kang J;Canales A;Fink Y;Choi GB;Zhao X;Anikeeva P
• 通讯作者: Anikeeva P

EML webinar overview: Extreme mechanics of soft materials for merging human–machine​ intelligence

• DOI: 10.1016/j.eml.2020.100784
• 发表时间: 2020-09
• 期刊: Extreme Mechanics Letters
• 影响因子: 4.7
• 作者: Xuanhe Zhao