Collaborative grant will fund UC research on UAV navigation
The University of Cincinnati College of Engineering and Applied Science pursues innovative UAV solutions to mitigate risks for first responders
Manish Kumar, PhD, currently focuses on UAV prototypes. Photo/UC Creative Services
The University of Cincinnati College of Engineering and Applied Science is using drones to help mitigate risks for first responders.
Manish Kumar, Ph.D., a UC professor of mechanical engineering, is principal investigator on a team that received grant funding offered by the U.S. Department of Homeland Security Science and Technology Directorate First Responders Group, in collaboration with Smart City Internet of Things Innovation labs.
UC is one of 13 organizations to receive funding in the first phase of the project, and one of only two universities selected to receive funding for their research proposals. The UC proposal focuses on unmanned aerial systems for indoor search and discovery.
The goal of the project is to develop a prototype unmanned air vehicle (UAV) that can perform in conditions faced by first responders every day. Other areas of interest for the project include building sensors and mobile communications.
SCITI (pronounced “city”) labs is a smart city solutions innovation lab created in collaboration between the U.S. Department of Homeland Security's Science and Technology Directorate, TechNexus and Smart City Works. The labs facilitate the development and launch of emerging technology.
Smart city technology refers to an urban area that uses different types of electronic data collection sensors to supply information which is used to manage assets and resources efficiently. In this application, UAVs could be used to reduce the risks to health and safety associated with search and rescue, disaster response and other unpredictable situations.
Remote control vehicles have a limited range and can lose communication with the controller while inside buildings. UAVs and other devices usually use localization services (like GPS) to orient themselves. However, GPS does not work inside buildings, making the process of localization and autonomous drone operations very challenging.
If you want to go somewhere, you have to know where you are first. People do it easily, but with robots, it’s more complicated.
Manish Kumar, UC engineering professor
This requires a lot of orchestration. Kumar’s goal is for the UAV to orient itself and begin strategizing the way a trained professional would upon entering a hazardous area, but this requires a great deal of “if-then” decisions amid a lot of uncertainty.
Navigation and obstacle avoidance is difficult to automate. Conditions that first responders face such as smoke, dust and heat can complicate the usual operations of UAV and sensor technology.
It is never as simple as letting a drone loose in a burning building.
“If you want to go somewhere, you have to know where you are first. People do it easily, but with robots, it’s more complicated,” Kumar explained.
Many complicated systems and algorithms go into making this technology effective and viable for larger scale use.
Once inside the building or hazard area, the UAV needs to be able to detect and geo-tag key features of the space, discover any people or potential dangers, capture and store images of the interior and compile a map of the area. Once the UAV collects all this data, first responders could determine whether or not humans should enter and devise the safest path to their target.
UAVs today use video and laser detection to sense their surroundings, but these methods are less than effective when smoke, heat, dust, and other conditions obscure sensors. To circumvent these barriers, UC is experimenting with sonar technology. The UAV can detect and map its environment by using relative positioning signals.
Kumar’s team is working on Artificial Intelligence (AI) algorithms to quickly process the rapid-fire data being transferred from the UAV to the first responders. Survivor location and hazard assessment are just two ways that drones could potentially assist public safety professionals, but the applications are limitless.
Kumar’s team received funding in May for six months of development. The team will present a prototype after the close of fall 2018. If the prototype is approved, Kumar may receive more funding and move to the next phase of the project.
Kumar is optimistic. He is already planning phase two.
“Our demonstration to DHS in Chicago showed how our machine worked in smoke simulations,” Kumar said. “Next steps would include heat shielding and creating a more robust prototype that could potentially function in a real-time hazardous environment.”
Featured image at top: A UAV is demonstrated in Kumar's lab. Photo/UC Creative Services
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