Feature Matching Algorithms for Machine Vision Based Autonomous Aerial Refueling

In this paper a machine vision (MV) based system is proposed as distance estimation sensor to be employed by UAVs during the operations of autonomous aerial refueling. For studying this problem it was developed a simulator featuring a 3D virtual reality (VR) interface that generates the image stream of the AAR maneuver. The proposed MV algorithm performs specific tasks as image processing for features extraction, feature matching and pose estimation. The problem of tanker/UAV attitude estimation from images is investigated in two scenarios: with and without artificial markers installed on the tanker. Two feature matching algorithms are proposed and the performance of the optical feedback signal are analyzed and compared in closed loop simulations

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