EFRI C3 SoRo: Strong Soft Robots--Multiscale Burrowing and Inverse Design

EFRI C3 SoRo：强软体机器人——多尺度挖掘与逆向设计

• 批准号: 1830950
• 负责人: Timothy Kowalewski
• 金额: $ 197.75万
• 依托单位: University of Minnesota-Twin Cities
• 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: 2018-09-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830950&HistoricalAwards=false
• 关键词: EFRI; C3; SoRo; Strong; Soft

This project directly addresses major challenges facing the emerging field of soft robotics. Soft robots are made of inherently compliant materials that are soft, flexible, and move gracefully in three dimensions without requiring discrete joints. However, these highly compliant soft bodies may prove too weak to exert sufficiently large forces to accomplish desired tasks. Additionally, there is a general lack of understanding of how to best navigate the bewildering spectrum of materials, configurations, and designs available to soft robotics. This project explores the properties of 3D-printable polyurethane polymers that can be customized to provide different mechanical properties. This project will create mathematical models of highly deformable structures, and computational tools to solve the "inverse problem" of finding the material parameters and 3D printing pattern that achieve a specified structural behavior. The project will consider two currently infeasible tasks at greatly different length scales. Task 1 is a millimeter-scale patient-specific soft robot catheter for neurovascular and cardiovascular applications, where the robots can gently move through blood vessels without requiring risky surgery, blocking blood flow, or injuring the patient. Task 2 is a meter-scale robot that intelligently burrows underground, with force levels much higher than previously attained by soft robots. Soft robots in the vascular application can inform potential breakthroughs for the treatment of heart disease and stroke. Large burrowing robots could prove beneficial for inspecting underground civil infrastructure or laying new fiber optic cable, irrigation, or power lines. This project is also designed to engage high school students, and inspire them to pursue STEM careers, including future roboticists.This project will establish and validate a mathematical framework for the inverse design of universal soft robots that: 1) provide sophisticated 3-D kinematics by further generalizing fiber-reinforced elastomeric enclosures with beam elements and arbitrary shapes along with exceptional force and power densities that match well-known McKibben actuators; 2) achieve arbitrarily-specified tasks and performance requirements including novel multiscale burrowing behavior; and 3) dictate a new means of robotic, automated manufacturing via 3D printed materials exploiting highly anisotropic elastomers, inextensible fibers, and beam elements and their interfacial chemistries. This mathematical formalism generalizes traditional robot kinematics via a full body mapping incorporating dynamic, arbitrary shape sequences specified by an arbitrary desired task. The coupled innovation in polyurethane chemistry and manufacturing will enable soft robots that exceed the capabilities of existing soft robots and overcome fundamental limitations in their capacity to exert useful force, modulate stiffness, and achieve previously-impossible tasks. This project includes validation experiments on two specific testbeds: (1) millimeter-scale soft robot catheters that locomote through vascular networks, and (2) meter-scale burrowing robots in soils, capable of inferring soil properties to adapt their morphology and motion to suit conditions in naturally occurring, highly heterogeneous, soil deposits.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.

该项目直接解决了软机器人新兴领域面临的主要挑战。软机器人是由固有的柔性材料制成的，它们柔软、灵活，在三维空间中优雅地移动，而不需要离散的关节。然而，这些高度柔顺的软体可能太弱，无法施加足够大的力来完成预期的任务。此外，人们普遍缺乏对如何最好地驾驭可用于软机器人的令人眼花缭乱的材料、配置和设计的理解。该项目探索可定制的3d打印聚氨酯聚合物的性能，以提供不同的机械性能。该项目将创建高度可变形结构的数学模型，并使用计算工具来解决寻找材料参数和实现特定结构行为的3D打印图案的“逆问题”。该项目将考虑两项目前不可行的任务，其长度范围大不相同。任务1是一个毫米级的病人专用软机器人导管，用于神经血管和心血管应用，机器人可以轻轻地穿过血管，而不需要危险的手术，阻塞血液流动，或伤害病人。Task 2是一个米级的机器人，它可以智能地在地下挖洞，其力量水平远远高于以前的软机器人。软机器人在血管方面的应用可以为心脏病和中风的治疗带来潜在的突破。大型挖洞机器人可能有助于检查地下民用基础设施或铺设新的光纤电缆、灌溉或电力线。该项目还旨在吸引高中生，并激励他们从事STEM职业，包括未来的机器人专家。该项目将建立并验证通用软机器人逆向设计的数学框架：1)通过进一步推广具有梁单元和任意形状的纤维增强弹性体外壳，以及与著名的McKibben驱动器相匹配的特殊力和功率密度，提供复杂的三维运动学；2)实现任意指定的任务和性能要求，包括新颖的多尺度挖洞行为；3)通过3D打印材料，利用高度各向异性弹性体、不可扩展纤维和光束元件及其界面化学物质，提出了一种机器人自动化制造的新手段。这种数学形式通过包含由任意期望任务指定的动态任意形状序列的全身映射来推广传统机器人运动学。聚氨酯化学和制造方面的耦合创新将使软机器人超越现有软机器人的能力，并克服其在施加有用力，调节刚度和实现以前不可能完成的任务方面的基本限制。该项目包括两个特定试验台的验证实验：(1)毫米级软机器人导管，在血管网络中移动；(2)米级土壤挖洞机器人，能够推断土壤特性，以适应自然发生的高度不均匀的土壤沉积物的形态和运动。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

项目成果

Characterization of Mechanical Properties of a Synthetic Modeling Clay Used as a Substitute for Natural Soils

用作天然土壤替代品的合成造型粘土的力学性能表征

• DOI: 10.1061/9780784484036.008
• 发表时间: 2022
• 期刊: ASCE Geo-Congress 2022
• 作者: Lee, Hyunjin;Ponkshe, Nitish;Hambleton, James P.;Van de Ven, James D.
• 通讯作者: Van de Ven, James D.

Multi-material inverse design of soft deformable bodies via functional optimization

基于功能优化的软变形体多材料逆向设计

• DOI: 10.1088/1361-6420/acaa31
• 发表时间: 2023
• 期刊: Inverse Problems
• 影响因子: 2.1
• 作者: Awasthi, Chaitanya;Lamperski, Andrew;Kowalewski, Timothy M.
• 通讯作者: Kowalewski, Timothy M.

A Device for Reducing Pressure Ulcers in Bedridden Patients Using Fiber Reinforced Elastomeric Enclosures (FREEs)

使用纤维增强弹性体外壳（免费）减少卧床患者压疮的装置

• DOI: 10.1115/imece2022-95255
• 发表时间: 2022
• 期刊: and Complexity.
• 作者: Russo, Lea;Gondhalekar, Mihir;Kota, Sridhar;Bassin, Benjamin
• 通讯作者: Bassin, Benjamin

A Simple Free-Fold Test to Measure Bending Stiffness of Slender Soft Actuators

测量细长软执行器弯曲刚度的简单自由折叠测试

• DOI: 10.1109/lra.2021.3114960
• 发表时间: 2021
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: McDonald, Gillian J.;Detournay, Emmanuel;Kowalewski, Timothy M.
• 通讯作者: Kowalewski, Timothy M.

UV-Assisted Direct Ink Writing of Dual-Cure Polyurethanes

• DOI: 10.1021/acsapm.3c02806
• 发表时间: 2024-02
• 期刊: ACS Applied Polymer Materials
• 影响因子: 5
• 作者: Matthew M. Hausladen;Gabriela Diaz Gorbea;Lorraine F. Francis;Christopher J. Ellison