UK researcher receives NSF CAREER award to create safe, smart target drone capturing

A University of Kentucky researcher is creating innovative methods to make drones safer and smarter.

Xu Jin, Ph.D., assistant professor in the Department of Mechanical and Aerospace Engineering in the UK Stanley and Karen Pigman College of Engineering, has received the prestigious National Science Foundation (NSF) Faculty Early Career Development (CAREER) Award. The NSF will support Jin with $542,714 over five years for his research involving learning-based cooperative control algorithms for multi-agent systems to capture and manage target drones.

The drone industry is a multi-billion-dollar market, and affordable civilian drones are now widely accessible. However, increased drone usage has led to safety concerns such as unauthorized drones flying dangerously close to airports.

Jin’s research focuses on utilizing multiple unmanned aerial vehicles that work together to capture and remove drones from the sky using nets.

“We want to use multiple unmanned aerial vehicles, what we call UAVs, to collaboratively and autonomously put the drone out of the sky with a capture net carried by these unmanned aerial vehicles,” said Jin. “We have mainly two major technical difficulties. One, of course, is the safety concerns. We want to capture the drone, which means we must fly close to the target drone. But we do not want to collide with the drone. We want to ensure safety.”

Another technical difficulty is learning the target behavior.

“The target does not want to be captured. We must learn the target behavior, as well as to learn the environmental factors,” said Jin. “All these things must be taken into consideration by what we call ‘deep neural network learning’ which mimics human brain behavior.

“At the end of the five years, hopefully we will achieve a few things. We will hopefully bring low-cost, widely accessible technology to accomplish the mission of drone capturing for the civilian market. To achieve this, we will develop learning-based cooperative control algorithms for this kind of multi-agent system collaboration.”

The CAREER Award is one of the “most prestigious awards in support of the early career-development activities of those teacher-scholars who most effectively integrate research and education within the context of the mission of their organization,” according to NSF.

Jin said, “This award will also bring visibility to our research so that hopefully down the road, we will attract more contribution and collaboration from all over the country so that different people with similar interests can work together.”

This material is based upon work supported by the National Science Foundation under Cooperative Agreement No. 2336189. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.