CyberTraining: Implementation: Small: Harnessing the AI and Cyberinfrastructure Revolution for Advanced Cyber-Physical Robotics Education and Research

Advanced robots and cyber-physical systems are becoming increasingly important to science, engineering, and the future workforce. These systems combine artificial intelligence (AI), computing, sensing, communication, and physical devices, but many students and researchers lack access to the tools and training needed to work with them in realistic settings. This project addresses that gap by creating a CyberTraining program for AI robotics and cyber-physical systems. The project will prepare students and researchers to use modern cyberinfrastructure to design, test, and evaluate advanced robotics systems. It will expand access through reusable learning materials, remote workflows, mentorship, course integration, and outreach across multiple educational pathways. By strengthening the workforce for AI robotics and cyber-physical systems, the project supports national needs in science, engineering, economic competitiveness, and emerging technology education. This project will develop and implement a cross-disciplinary training framework that integrates cyberinfrastructure-enabled instruction, hands-on laboratories, digital twin environments, and mentored project-based learning. The training activities will cover AI robotics, cyber-physical systems, data-centric experimentation, human-in-the-loop systems, and networked robots. Participants will learn to execute, adapt, and document research-grade workflows using shared computing, simulation, and experimentation resources. The project will provide direct mentorship to a large group of core participants and will scale through integration of the training modules into existing courses at the lead and partner institutions, reaching more than 6,500 students across engineering and computing disciplines. The project will produce reusable instructional modules, datasets, executable notebooks, simulation workflows, and documented examples that can be adopted by other institutions. These activities will establish a sustainable pipeline of students and researchers who can use, contribute to, and advance cyberinfrastructure for AI robotics and cyber-physical systems. 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. NSF Award ID: 2612474 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Xiangnan Zhong | Institution: Florida Atlantic University, BOCA RATON, FL | Award Amount: $499,998 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2612474 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2612474.html