�鶹��Ʒ��Ƶ| FAU's CA-AI Secures $2.2M AFRL Grant for Next-Gen Autonomous Systems

FAU's CA-AI Secures $2.2M AFRL Grant for Next-Gen Autonomous Systems

Researcher, Lab

Dimitris Pados, Ph.D., (left) principal investigator and director of FAU's Center for Connected Autonomy and Artificial Intelligence. (Photo by Alex Dolce)

By gisele galoustian | 5/14/2026

Award Snapshot: As autonomous technologies continue to expand their presence across commercial and defense applications, a critical limitation persists. While today’s machines can operate intelligently on their own, they often struggle to collaborate effectively as part of a network. This gap – where systems are individually smart but collectively deficient – limits their ability to function reliably in complex, real-world environments where team coordination, adaptability and resilience are essential. Overcoming this challenge is key to enabling the next generation of intelligent systems capable of sensing, learning and acting together in real time.

To address this gap, FAU’s Center for Connected Autonomy and Artificial Intelligence (CA-AI) in the College of Engineering and Computer Science has been awarded a $2,250,000 grant from the U.S. Air Force Research Laboratory (AFRL) to develop advanced networks of autonomous systems that operate collaboratively. In partnership with the University at Buffalo, the team, led by FAU’s Dimitris Pados, Ph.D., is designing systems that can perform distributed sensing and AI inference directly on board, dynamically adapt communications to each other to avoid interference, and make real-time decisions in contested environments. The project builds on breakthrough research, which is supported by more than $8 million in prior AFRL investment between the institutions, firmly placing CA-AI and �鶹��Ʒ��Ƶat the forefront of next-generation autonomous systems research.

As autonomous technologies continue to expand their presence across commercial and defense applications, a critical limitation persists. While today’s machines can operate intelligently on their own, they often fail to collaborate effectively as part of a network. This gap – where systems are individually smart but collectively deficient – poses a significant barrier to carrying out autonomous operations in complex and contested environments.

Overcoming this challenge is essential to unlocking the next generation of autonomous intelligence capable of sensing, learning and acting in coordination.

To address this critical need, the Center for Connected Autonomy and Artificial Intelligence (CA-AI) in the College of Engineering and Computer Science at �鶹��Ʒ��Ƶ has been awarded a $2,250,000 grant from the United States Air Force Research Laboratory (AFRL) to develop advanced networks of autonomous systems that can operate collaboratively. The project brings together FAU, the University at Buffalo (UB), and the University of Minnesota, combining strengths in intelligent wireless systems, edge AI technology, swarm networking and large-scale testing environments.

“We’re investigating how connected AI machines and robots can operate together to solve complex problems,” said Dimitris Pados, Ph.D., principal investigator, director of the CA-AI, the Charles E. Schmidt Eminent Scholar in Engineering in the College of Engineering and Computer Science, and a fellow of FAU’s Sensing Institute (I-SENSE). “To realize the vision of AI autonomous systems, we must transition from smart units to intelligent, coordinated collectives.”

At the core of the project is a shift away from reliance on cloud computing toward networked edge-AI, where autonomous systems perform distributed sensing and AI inference directly on board while communicating with one another. These systems are designed to function like coordinated teams, enabling machines to share information, make decisions collectively and respond dynamically to changing conditions.

Pados and the research team are developing machine learning technologies that allow systems to sense the spectral environment and automatically adapt how they communicate, avoiding interference and maintaining strong, secure connections even in highly contested or degraded conditions. By embedding AI directly into wireless communication systems, the team is enabling machines to make real-time decisions about how to transmit data and support distributed intelligence across the network.

The work represents a significant technical advancement, building on new theory, methods and demonstrations, which have been highlighted in Nature Reviews as a breakthrough in the field.

The research is organized around three major areas: the development of secure networked edge-AI algorithms for learning and inference; the implementation of these capabilities directly into hardware systems spanning processors, GPUs and FPGAs from antenna to application; and a comprehensive workforce development effort that trains students from high school through the doctoral level in next-generation AI-driven networking and robotics. Collectively, these efforts aim to accelerate the transition of foundational research into deployable technologies for critical national applications.

“This award reflects the pioneering research taking place within our College of Engineering and Computer Science and reinforces �鶹��Ʒ��Ƶ’s role as a leader in next-generation technologies,” said Stella Batalama, Ph.D., dean of the College of Engineering and Computer Science. “The ability for autonomous systems to communicate, learn and adapt collaboratively will redefine the future of intelligent systems and strengthen our nation’s technological leadership and security.”

Over the past several years, the AFRL has invested more than $8 million in joint research efforts between �鶹��Ʒ��Ƶand UB, supporting advances in smart, programmable wireless networking and laying the groundwork for this next phase focused on fully integrated, AI-enabled autonomous systems.

The project will also focus on scaling these technologies into increasingly complex, real-world environments while expanding education and workforce training initiatives. Students at all levels will gain hands-on experience designing, testing and deploying AI-enabled networked systems, helping to build a pipeline of talent equipped to lead in the rapidly evolving fields of autonomous systems and intelligent communications.

CA-AI serves as a hub for this work, bringing together expertise in AI-enabled technologies, machine learning, cognitive radio, secure wireless communications and software-defined radio systems. The center has established itself as a leader in developing autonomous, wireless-networked robotic systems capable of operating in challenging and dynamic communication environments, supported by advanced testbeds and real-world simulation platforms.

-FAU-