Autonomous System for Rapid Airfield Assessment

K. Teope, M. Anderson, D. Jensen
US Air Force Academy, Colorado, United States

Keywords: runway regeneration, UAS, autonomous, airfield assessment

One of the Air Force’s top science and technology challenges is the regeneration of sorties after an airfield has been attacked. The current method is slow: First, airmen drive the airstrip, recording the positions of debris, damage and unexploded ordinance (UXO). Next UXO and debris are cleared, and finally, the damage is repaired. In this work, we sought a Remotely-Piloted Aircraft (RPA)-based solution to improve this process. Improving the assessment portion of the regeneration problem would provide the greatest immediate impact, so a team of semi-autonomous quad-rotor UAVs with optical and thermal sensors was proposed. An algorithm was implemented that automatically detects deviations in the thermal imagery, extracts GPS data from the optical data and places it on a map that displays damages and locations directly to the warfighter in the operations center.