Yingbin Liang leads NSF RINGS Project to Advance Unmanned Aerial Vehicle Networks

Posted: July 12, 2022
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Creating trust and security in the realm of unmanned aerial vehicles (UAVs) poses unique engineering design challenges. Ohio State University faculty just earned a boost of support to help advance the momentum.

The National Science Foundation Resilient and Intelligent NextG Systems (RINGS) program awarded $1 million to a research project led by Electrical and Computer Engineering Professor Yingbin Liang and other affiliated universities.

The research, “RINGS: A Deep Reinforcement Learning Enabled Large-scale UAV Network with Distributed Navigation, Mobility Control, and Resilience" is being conducted jointly with Professor Junshan Zhang of University of California-Davis, Professor Hai (Helen) Li of Duke University and Professor Qinru Qiu of Syracuse University.

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Liang explained UAVs are aircrafts piloted by remote control or embedded computer programs without a human pilot on-board. The increasing demand and safety of these machines require preparation.

“There is explosive growth of UAVs, recently in civilian and commercial applications – such as aerial inspection, package delivery, photography, precision agriculture, traffic control, search and rescue, and telecommunications,” Liang said.

The RINGS program aims to accelerate research in emerging Next Generation (NextG) wireless networks and systems. The goal is to develop various foundational technologies in order to enable UAVs to have strong sensing, communications, and on-board computing capabilities.

“All of these developments are for UAVs to adapt rapidly to the dynamically changing environment, to be resilient to extreme environmental conditions, and to be secure against data contamination and malicious attacks,” Liang said.

Ultimately, each UAV mission involves unique design challenges facing an unforeseen future.

“In order for UAVs to successfully accomplish their missions, technology must include continuous sensing of the environment, as well as complicated traffic scenes, real-time mobility control with ultra-low latency, hardware-aware on-board efficient computation, strong system resilience and defense functions,” Liang said.

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