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Drones will help drivers on the ground determine their vehicle’s position in the absence of GPS signals. The technologies are expected to translate to a wide range of problems from autonomous driving to border security to disaster response.
The U.S. Army Research Lab awarded the University of Central Florida a $4.5 million grant to develop a smart, computer vision-based navigation system for when GPS is unavailable or jammed. The system will use artificial intelligence and machine learning to assess computer images captured by the vehicle and by unmanned aerial vehicles (UAVs). It will help drivers determine where they are and how to get to where they are going in complex terrain.
The system will use geospatial databases to identify landmarks for correlation to imagery and will track object movements through video to estimate motion. The researchers will combine these techniques using artificial intelligence to do this precisely and autonomously.
In addition to navigating in GPS-denied environments wherein adversaries can jam or spoof GPS signals, the project is “also about supporting ground vehicles with off-board sensors on UAVs that can provide additional perspectives for awareness and threat detection in complex, typically urban, scenarios,” says Kyle Renshaw, the project’s principal investigator and an assistant professor in UCF’s College of Optics and Photonics (CREOL).
Also participating is UCF’s Center for Research in Computer Vision (CRCV). Its researchers will develop algorithms to automatically analyze the data collected by the CREOL team to extract relevant features from mission imagery in order to match with geo-tagged reference imagery for GPS denied combat navigation, according to insidegnss.com.