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

点击翻译按钮获取中文摘要

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.