National Science Foundation grant to fund drone advances at UNT
The National Science Foundation has awarded Shengli Fu, UNT's College of Engineering associate professor and chair of electrical engineering, a $250,000 grant for drone research and development. The grant is part of $1 million that has been divided between UNT, the University of Texas at Arlington, Texas A&M University – Corpus Christi and the University of Puerto Rico at Mayagüez.
"I'm excited about the potential for this grant," Fu says. "There is a significant need to improve drone techniques for research. The current 'out-of-the-box' designs only allow for video and photography. We need drones that can accomplish more – communication, control, computation and networking."
The three-year grant will allow Fu to create an open platform drone for testing by researchers in computer and information science and engineering. Fu will provide testers with information on assembly, calibration and flight instructions and build central processing units for the drones that allow for researchers to completely customize their usage through applications they develop.
"This will be a plug-and-play design that will allow researchers to access all technology that meets their needs via an app-like interface," Fu says. "With the open platform, researchers will save time and money by tailoring an existing drone's CPU to fit their needs – such as adding sensors or transmitters to send information back to the operators and any other equipment required to meet their specific requirements."
Fu says the technology can be used for anything from emergency response to agriculture monitoring and environmental testing.
"We want the ability for multiple drones to handle one mission – drones that can work as a network so if one fails, the others can continue the task," Fu says. "An example is environmental monitoring, where air quality tends to be tested by ground sensors due to the cost to elevate them. These drones would allow for elevation of sensors for real-time readings by multiple sources over a wider area, improving accuracy."
Fu plans to finalize his initial prototype in early 2018.