Onboard monocular vision for landing of an MAV on a landing site specified by a single reference image

This paper presents a real-time monocular vision solution for MAVs to autonomously search for and land on an arbitrary landing site. The autonomous MAV is provided with only one single reference image of the landing site with an unknown size before initiating this task. To search for such landing sites, we extend a well-known visual SLAM algorithm that enables autonomous navigation of the MAV in unknown environments. A multi-scale ORB feature based method is implemented and integrated into the SLAM framework for landing site detection. We use a RANSAC-based method to locate the landing site within the map of the SLAM system, taking advantage of those map points associated with the detected landing site. We demonstrate the efficiency of the presented vision system in autonomous flight, and compare its accuracy with ground truth data provided by an external tracking system.