The field of soft robotics is growing rapidly in recent years, with the rising demand for advanced robotic systems to operate efficiently, robustly, intelligently, and safely under unstructured environments. Compared to traditional rigid robotic systems, soft robots are highly dexterous in the sense that they can deform their soft body to adapt to clustered environments without damage or jamming. In addition, soft robots can be made to be low-cost, low-power, lightweight, and human friendly, promoting many applications that are otherwise not available, such as picking up fragile objects (e.g., tomatoes) in agriculture harvesting, non-invasive endoscopic surgery in medical applications, and soft robotic grippers in deep-sea exploration, etc. However, implementation of soft robots in real-world applications presents challenges in many technological aspects, including material, sensing, modeling, and control. The research of soft robotics is still in its primitive stage as a unified framework for the design, modeling, and control of highly dexterous soft robots is still lacking. This project supports fundamental research to provide the knowledge needed to fill this important technology void, so as to promote a wide range of soft robot applications, e.g., in-space/underwater exploration, aerospace, healthcare, biomedical, and agricultural industries. Therefore, results from this research will not only promote the progress of robotics science and engineering, but also benefit the U.S. economy, society, and national defense. This research involves multiple disciplines including robotics, control theory, machine learning, computational mechanics, and material science. The interdisciplinary approach will help boost minority involvement in scientific research and promote engineering education.
The goal of this project is to investigate an efficient and accurate dynamics modeling and control framework for soft robotic manipulation and locomotion under unstructured environments. Specifically, the research team will develop modular plug-and-play soft robotic arms with distributed power, actuation, and tactile sensing. A three-dimensional, reduced-order, geometrically exact, finite element model of soft robotic arms with internal actuation forces from tendon contraction will be formulated and implemented. An efficient and accurate simulation program for the dynamics of soft robots interacting with the environments will be developed. Dynamic controllers, hybridizing model-based and data-driven control strategies, will also be devised and tested. Through a series of simulations and physical experiments, the team will identify fundamental design principles and develop controllers for enabling autonomous soft robots such as elephant trunk-like dexterous soft manipulators and octopus-like walking/swimming soft robots.
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.
