Collaborative Research: Adaptive, Rapid, and Multifunctional Soft Robots (ARM SoRo) with Reconfigurable Shapes and Motions Enabled by Tunable Elastic Instabilities

协作研究：具有可重构形状和运动的自适应、快速和多功能软机器人 (ARM SoRo)，由可调弹性不稳定性实现

基本信息

批准号：
2126072
负责人：
Jie Yin
金额：
$ 31.71万
依托单位：
North Carolina State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-12-01 至 2024-11-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2126072&HistoricalAwards=false
关键词：
Collaborative Research Adaptive Rapid Multifunctional

项目摘要

Robots made of metals, hard plastics, or similarly high stiffness materials are restricted in range of motion and shape changes. It would be extremely beneficial if a robot could be reconfigured on-the-fly to generate on-demand shapes and motions required for various tasks such as walking, crawling, and jumping. This award supports fundamental research on how to leverage mechanical modules with elastic instabilities, e.g., bistable modules that can rapidly switch between two stable states, to spontaneously reconfigure a robot’s shape and motion. The research will also develop novel robots with multi-modal locomotion capabilities that can adapt to environments without modifying their mechanical structure. The resulting knowledge will advance the national health and benefit the society in unprecedented ways ranging from search-and-rescue in disasters (e.g., earthquakes) to monitoring in hazardous environments (e.g., nuclear plants). Additionally, this award will offer a unique opportunity to integrate insights from robotics, mechanics, design, and fabrication into intellectually intriguing and visually appealing broadening participation activities to inspire, engage, and educate students and the public alike, with the science and technology of reconfigurable robots. Examples of activities include senior design projects, summer program for high school students, and science and engineering festival.The objective of this research is to gain a fundamental understanding of a new class of soft robots made from soft/flexible modules with elastic instabilities. The goal is to enable soft robots with reconfigurable body shapes and leg motions for multimodal locomotion that can adapt to various complex environments. The strategy is to construct the robots using bistable modules connected in a closed loop for the body and an open loop for the legs, and then actively tune the energy landscape of each module on-the-fly to generate desired body shapes and leg motions for multimodal locomotion. Three research thrusts will be explored: 1) achievement of reconfigurable body shapes through an in-depth understanding of the energy landscapes of bistable modules via the use of quasi-static mechanics; 2) achievement of programmable motions through physics-based dynamics modeling using Cosserat rod theory and model-based reinforcement learning; and 3) validation of the models with the development of a robot with multimodal locomotion capabilities, such as walking, crawling, jumping, and climbing. The knowledge generated from this project will provide guidelines on how to systematically exploit elastic instabilities to generate programmable shapes and dynamic motions. This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).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.

由金属，硬塑料或类似高刚度材料制成的机器人受到运动和形状变化范围的限制。如果可以将机器人在现场重新配置以产生按需形状和动作（例如步行，爬行和跳跃所需的动作），那将是非常有益的。该奖项支持有关如何利用弹性不稳定性来利用机械模块的基础研究，例如，可在两个稳定状态之间迅速切换的可稳定模块，以赞助重新配置机器人的形状和运动。这项研究还将开发具有多模式运动能力的新型机器人，可以适应环境而不修改其机械结构。所产生的知识将促进民族健康，并以前所未有的方式使社会受益，从灾难中的搜索和救援（例如，地震）到监测危险环境（例如核电站）。此外，该奖项将提供一个独特的机会，将机器人，机械师，设计和制造的见解融为一体，以智能和视觉上出现的宽广的参与活动，以激发，互动和教育的学生以及公众以及可重新配置的机器人的科学和技术。活动的例子包括高级设计项目，针对高中生的夏季计划以及科学与工程节。这项研究的目的是对由具有弹性不稳定性的软/柔性模块制成的新的软机器人进行基本了解。目的是通过可重新配置的身体形状和腿部运动来启用可以适应各种复杂环境的多模式运动的软机器人。该策略是使用连接到身体的封闭环和腿部的闭环中的双态模块来构建机器人，然后积极地调整每个模块的能量景观，以生成多模束运动的所需身体形状和腿部运动。将探讨三个研究推力：1）通过使用准静态力学对Biscable模块的能量景观的深入了解，实现了可重构身体形状的实现； 2）通过使用Cosserat Rod理论和基于模型的增强学习的基于物理的动力学建模来实现可编程动作； 3）通过开发具有多模式运动功能的机器人的验证，例如步行，爬行，跳跃和攀爬。该项目产生的知识将提供有关如何系统利用弹性不稳定性以生成可编程形状和动态动作的指南。该项目得到了机器人技术计划中的跨指导基础研究的支持，该研究由工程局（ENG）以及计算机和信息科学与工程局（CISE）共同管理和资助。该奖项反映了NSF的法定任务，并已通过评估基金会的知识和更广泛的影响来诚实地通过评估来诚实地支持。