Conference Publication

D. Cazzato, M. A. Olivares-Mendez, J. L. Sanchez-Lopez, H. Voos. Vision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers. 45th Annual Conference of the IEEE Industrial Electronics Society (IECON 2019). IEEE. e-ISSN: 2577-1647. Dec. 2019. (Online: Dec. 2019). DOI: 10.1109/IECON.2019.8926667.

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Abstract:
The reliability of aircraft inspection is of paramount importance to safety of flights. Continuing airworthiness of aircraft structures is largely based upon the visual detection of small defects made by trained inspection personnel with expensive, critical and time consuming tasks. At this aim, Unmanned Aerial Vehicles (UAVs) can be used for autonomous inspections, as long as it is possible to localize the target while flying around it and correct the position. This work proposes a solution to detect the airplane pose with regards to the UAVs position while flying autonomously around the airframe at close range for visual inspection tasks. The system works by processing images coming from an RGB camera mounted on board, comparing incoming frames with a database of natural landmarks whose position on the airframe surface is known. The solution has been tested in real UAV flight scenarios, showing its effectiveness in localizing the pose with high precision. The advantages of the proposed methods are of industrial interest since we remove many constraint that are present in the state of the art solutions.