Date of Award
3-19-2020
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Department of Electrical and Computer Engineering
First Advisor
Clark N. Taylor, PhD
Abstract
Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. The analysis focuses on the effects of camera positioning with the rear-facing stereo vision system. In particular, the research seeks the optimal system design for the camera system to achieve the most accurate navigational estimates. The testing process consists of utilizing a simulation engine and recreating real world flights based on previously collected Global Positioning System (GPS) data. Using the pose estimation results and the ground truth information, the system computes the error between the incoming aircraft's position in the virtual world and its calculated location based on the stereo matching algorithm. The testing process includes both un-obscured scenarios and cases where the boom causes significant occlusions in the camera images. The results define the improvements in position and orientation estimation of camera positioning from the consolidated simulation data. Conclusions drawn from this research will propose and help provide recommendations for future Air Force acquisition and development of aerial refueling systems.
AFIT Designator
AFIT-ENG-MS-20-M-059
DTIC Accession Number
AD1103189
Recommended Citation
Sarantsev, Kirill A., "Maximizing Accuracy through Stereo Vision Camera Positioning for Automated Aerial Refueling" (2020). Theses and Dissertations. 3270.
https://scholar.afit.edu/etd/3270