Panos Pardalos, Ph.D., Receives Funding for Research in Navigation Approaches for Autonomous Vehicles
Panos Pardalos, Ph.D., distinguished professor of Industrial & Systems Engineering, in the Department of Industrial & Systems Engineering, received funding from the U.S. Air Force Research Laboratory Munitions Directorate. The funding supports Dr. Pardalos’ research to develop deep learning navigation applications with synthetic aperture radar (SAR) image data used by unmanned aerial vehicles.
An unmanned aerial vehicle (UAV) is an aircraft that is guided either autonomously or by remote control. The military uses UAVs to carry sensors and other electronic transmitters that can detect enemy targets. These UAVs rely on an embedded global positioning system (GPS) that provides position, navigation, and timing information. However, when in a GPS-denied environment, UAVs need to rely on other mechanisms.
“Conventionally, UAVs or airplanes rely on information from GPS dominantly when acquiring information on geographic coordinates for navigation. Our research focuses on developing a deep learning-based system for image recognition that enables navigation in a region where GPS is not available. We also utilize the SAR images that can be acquired, regardless of the weather conditions, as data for training the deep learning system,” said Dr. Pardalos. “To this end, we need to build the deep learning system that enables real-time calculation as well as accurate SAR image recognition.”
Learn more about Panos Pardalos, Ph.D., Receives Funding for Research in Navigation Approaches for Autonomous Vehicles.