AI and Robotics for Digital Twins in Civil Infrastructure
Explore the frontier of AI and robotics applied to civil infrastructure diagnostics and retrofitting using digital twin technology. Develop autonomous systems and simulation analytics to improve infrastructure resilience and sustainability.
AI-generated overview
Project Description
Project Overview
This PhD project explores the integration of artificial intelligence, robotics, and digital twin technologies to innovate civil infrastructure. Key objectives include developing intelligent autonomous systems for infrastructure diagnostics, performance simulations, and retrofitting tasks using real-to-sim-real digital twins and multimodal data fusion.
What You Will Do
- Develop real-to-sim-real digital twins for multi-modal data fusion and simulation analytics.
- Create AI-enabled robotic systems incorporating autonomous capabilities and human-AI-robot collaboration.
- Engage in community-driven research to facilitate technology transfer in civil infrastructure.
Expected Outcomes
The work will yield advanced tools and methodologies for monitoring and maintaining critical infrastructure with improved efficiency, safety, and sustainability. The integration of AI-enabled robotics will enable scalable diagnostics and retrofitting aligned with urbanization and climate change challenges.
Why This Matters
With infrastructure facing increasing demands, this research offers innovative solutions addressing maintenance, resilience, and sustainability. The multidisciplinary approach combining AI, robotics, and civil engineering will contribute to safer, more cost-effective infrastructure systems with tangible societal benefits.