Robotic Materials for Future Infrastructure

Ahmed Elbanna & Ann Sychterz (Civil & Environmental Engineering)
Sameh Tawfick & Kathryn Matlack (Mechanical Sci & Engineering)
Jeff Shamma (Industrial & Enterprise Systems Engineering)

Research Problem 

Significant advances in sensing and data acquisition for built infrastructure must be more cohesive and separate from advances in on-demand computation and decision-making. The current state-of-the-art thus needs compatibility that would foster holistic approaches to translate data into actions by advancing active control facilitated by fast computation and actuation of infrastructure to mitigate episodic (extreme events) and periodic events (climate change and seasonal impacts) as they occur in real-time. Future-built infrastructure should have the framework for integrating different data streams from sensor PI: ELBANNA 2 networks, distributed computing using built-in processors, machine learning for fast decision-making and distributed control, and actuation for fast recognition and response to rapidly changing environmental or loading conditions.

Vision

Through a research thrust, identify fundamental challenges and potential solutions in modeling, manufacturing, and realization of active materials at scale. Through an outreach thrust, build collaboration networks and develop new training paradigms.

Larger Impact

The success of this project will place UIUC as the leader and catalyze significant funding efforts from industry and federal agencies. The robotic material framework envisioned here revolutionizes future smart cities by expanding the concept of autonomy to the built infrastructure, including buildings, bridges, and roads. This project will also contribute to the fundamental understanding of active matter, including discovering new rules for self-assembly and reconfigurability and balance laws and constitutive descriptions for this new class of material systems from elasticity to damage.