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

由金属、硬塑料或类似的高刚度材料制成的机器人在运动范围和形状变化方面受到限制。如果一个机器人可以在飞行中重新配置，以产生各种任务所需的形状和动作，如行走、爬行和跳跃，这将是非常有益的。该奖项支持关于如何利用具有弹性不稳定性的机械模块的基础研究，例如，可以在两个稳定状态之间快速切换的双稳态模块，以自发地重新配置机器人的形状和运动。该研究还将开发具有多模式运动能力的新型机器人，这些机器人可以在不改变其机械结构的情况下适应环境。由此产生的知识将促进国民健康，并以前所未有的方式造福社会，从灾难（如地震）中的搜索和救援到危险环境（如核电站）中的监测。此外，该奖项将提供一个独特的机会，将机器人、机械、设计和制造的见解整合到智力上有趣和视觉上吸引人的领域，扩大参与活动，以激发、参与和教育学生和公众，利用可重构机器人的科学和技术。活动的例子包括高级设计项目、高中生暑期项目和科学与工程节。本研究的目的是对一类由具有弹性不稳定性的软/柔性模块制成的新型软机器人有一个基本的了解。目标是使软体机器人具有可重构的身体形状和腿部运动，能够适应各种复杂环境的多模式运动。该策略是使用双稳态模块构建机器人，身体以闭环连接，腿部以开环连接，然后动态调整每个模块的能量格局，以产生所需的多模式运动的身体形状和腿部运动。将探讨三个研究重点：1)通过使用准静态力学，通过深入了解双稳态模块的能量景观，实现可重构的车身形状；2)利用Cosserat杆理论和基于模型的强化学习，通过基于物理的动力学建模实现可编程运动；3)通过开发具有行走、爬行、跳跃和攀爬等多模式运动能力的机器人对模型进行验证。从这个项目中产生的知识将为如何系统地利用弹性不稳定性来生成可编程的形状和动态运动提供指导。该项目由跨部门机器人基础研究项目支持，由工程（ENG）和计算机与信息科学与工程（CISE）联合管理和资助。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。

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.