Exploiting Multi-Stability to Enable Mechanical Intelligence for Versatile and Efficient Control of Soft Robotic Locomotion and Manipulation

This project supports the fundamental research that aims to harness elastic multi-stability and transform the design and dynamic control of compliant and continuous robots (aka. "soft robots"). The ongoing advances in bio-mimicry, material science, fabrication technology, and control theory are enabling us to build genuinely soft robots that can collaborate with humans in unstructured and dynamic task environments. These robots are significantly superior and safer than the traditional rigid robots in disaster relief efforts, minimal-invasive surgeries, and assistive healthcare. However, the compliant and continuous nature of soft robots, as well as the fact that they are severely underactuated, imposes significant challenges for effective dynamic modeling and control. This research will, for the first time, systematically examine the use of multi-stability in soft robots to address these critical challenges. Multi-stability can create a "mechanical intelligence" in the body of a soft robot because it can coordinate (or sequence) the robotic motion and re-configure the state-space without relying on any digital controllers. In this way, one can directly "outsource" the low-level control tasks to the robotic body and formulate a hybrid mechanical-digital approach for dynamic modeling and control with unprecedented efficiency and effectiveness. The project will also sup-port different educational activities, such as using origami folded robots as the teaching tool, to in-spire and prepare students for their future career in the Science, Technology, Engineering, and Mathematics fields. This research will formulate an integrated framework, e.g., dynamic modeling, design, and fabrica-tion,- to unleash the potential of the aforementioned mechanical intelligence by multi-stability. The research team will use origami as the physical platform and complete a hierarchy of research tasks: 1) modeling and fabrication of robotic modules with prescribed and adaptive bi-stability; 2) design and validation of robotic components with embedded mechanical intelligence, and 3) con-struction of full robots with an interface between mechanical and digital intelligence. To complete these research tasks, the research team will derive new dynamic models for the bistable origami modules by expanding the absolute nodal coordinate formulation, develop design methodologies based on multi-objective optimization algorithms, and use responsive materials such as shape memory polymers to ensure the versatility and robustness of mechanical intelligence. Upon com-pletion, the research team will deliver demonstration robots that exploit the hybrid mechanical-digital intelligence for locomotion or manipulation. In these robots, the lower-level control tasks (such as locomotion gait generation) are executed by the embedded intelligence in the mechanical domain, while the high-level tasks (such as changing locomotion direction and speed according to the working environment) are achieved by sensors and controllers in the digital domain. 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.