The understanding of designing structured surfaces for advanced functionality, such as friction reduction, antifouling, and hydrophobicity, has significantly progressed over the years; however, the critical technical barrier to the application of these structured surfaces is the scalability in manufacturing capability. The biggest challenge in surface patterning is the process scalability, which needs to reconcile the significant scale difference between the individual feature size down to the nano- or micro-level and the large surface-to-be-textured up to the meter level. The project will investigate one vision for future manufacturing -- distributed robotic manufacturing -- to achieve scalable patterning of micro-structured functional surfaces using a cohort of mini-robots. The project will not only push the knowledge boundaries in the scientific understanding of distributed physical intelligence, machine-material interactions, and swarm control, but may open up a new and interdisciplinary research field at the intersection of manufacturing, robotics, control, and cyberphysical systems. Additionally, the project includes outreach at the Museum of Science and Industry in Chicago, open-source software, and curricular innovations, including online classes and training modules. The research will build an educational and outreach platform to enable education and workforce development for STEM educators, next generation workforce, and technical engineers.

The research objectives are to explore and answer three fundamental scientific questions that will enable the vision for future manufacturing in distributed robotic manufacturing. (1) Distributed physical intelligence: a new design framework will be established to distribute the intelligence among mechanical structures, analog circuits, and digital logics, as well as to design unconventional communication channels through both active and passive manners. (2) Unconventional machine-material interaction: new theoretical underpinnings will be established to investigate the machine-material interaction and the possible removal, deformation, and addition of material in this new paradigm, where the tools are extremely flexible and with significantly constrained power. (3) Swarm control: new fundamental knowledge will be generated from novel task decomposition and distribution paradigms to synthesis techniques capable of minimizing control effort, communication, and computation. Instead of top-down control of every individual mini-robot, novel methods will be established through which local rule specifications lead to global distributed pattern completion.

This Future Manufacturing award is supported by the Division of Computer and Network Systems (CNS) of the Directorate for Computer and Information Science and Engineering (CISE), and by the Division of Civil, Mechanical and Manufacturing Innovation (CMMI) of the Directorate for Engineering (ENG).