Date of Award
Master of Science in Computer Science
Department of Electrical and Computer Engineering
Scott L. Nykl, PhD
The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection and ranging (LiDAR) to create a relative pose estimation of the UAV and compares it to previous stereo vision results. Researchers at the Air Force Institute of Technology (AFIT) developed an algorithm to automate the refueling operation based on a stereo-vision system. While the system works, it requires a large amount of processing; it must detect an aircraft, compose an image between the two cameras' points of view, create a point cloud of the image, and run a point cloud alignment algorithm to match the point cloud to a reference model. These complex steps require a large amount of processing power and are subject to noise and processing artifacts.
Crowl, Michael R., "Use of LiDAR in Automated Aerial Refueling To Improve Stereo Vision Systems" (2020). Theses and Dissertations. 3171.