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.

该项目将创建一类新的亚毫米表手术软机器人，该机器人能够在人体中进行不受限制的操作，并通过旨在以不同方式对外部磁场做出反应的软功能材料的可编程域来实现。这些材料可用于推动和引导机器人或触发永久形状变化，并通过强迫场的频率选择不同的功能。其他材料域旨在通过更改电子性质来提供分布式感应。在系统级别上，基于模型和数据驱动的方法将根据机器人传感器的实时透视图像和信息来调节外部磁场以控制机器人的机器人。机器人性能将经过实验验证，包括在动物模型中。结果将提高到常规技术的准确性，可施加性和可通道性，从而为现有的手术机器人或机器人导管无法访问复杂和约束的环境。这些新机器人将为最小的侵入性手术开放新场地，并有可能解决长期以来的挑战和未满足的医疗保健需求。该项目将由具有互补专业知识的研究人员团队进行，包括软活动材料设计和制造，组成型建模和力学，灵活的电子和传感器，机器学习和数据处理，医疗设备设计以及转化医学。该项目将为来自代表性不足的团体的毕业，本科和高中生提供研究和培训机会，并将为K-12学生提供研讨会和研讨会。Soft机器人目前面临着一系列关键挑战控制和小型化。该项目旨在通过范式转移功能域方法来应对挑战，以设计，制造和控制新的功能域软机器人（Fundo Soro）。具有可编程驱动的独立多功能域以及用于准确动态控制的分布式感应和数据驱动策略的Indo Soro将代表软机器人技术的设计，制造和控制中的新范式。实现Indo Soro的具体方法是1）开发新型的功能材料和多物质3D打印技术，以实现基于磁场的远程驱动，形状 - 重新配置，并通过一组对静态磁场的响应响应的集成驱动域，以及分布式感测。形状内存域可在动态磁场下重新配置，并能够测量应变，接触压力和温度的传感域； 2）开发理论和计算模型，以定量预测驱动时基金会的动态响应，以及通过机器学习辅助的数据驱动策略，以准确控制Fundo Soro的动态； 3）实验验证亚毫米软连续机器人，以减少侵入性的程序，以解决诸如脑动脉瘤或阻塞性肺部疾病等医疗保健中未满足的需求和挑战。该奖项反映了NSF的法规任务，并被认为是通过基金会的智力优点通过评估来支持的，和更广泛的影响审查标准。

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