Enabling aircraft emergency landings using active visual site detection

Warren, Michael, Mejias, Luis, Yang, Xilin, Arain, Bilal, Gonzalez, Felipe, & Upcroft, Ben (2013) Enabling aircraft emergency landings using active visual site detection. In Corke, Peter, Mejias, Luis, & Roberts, Jonathan (Eds.) FSR2013 The 9th International Conference on Field and Service Robotics, 9-11 December 2013, Brisbane, Australia.


The ability to automate forced landings in an emergency such as engine failure is an essential ability to improve the safety of Unmanned Aerial Vehicles operating in General Aviation airspace. By using active vision to detect safe landing zones below the aircraft, the reliability and safety of such systems is vastly improved by gathering up-to-the-minute information about the ground environment. This paper presents the Site Detection System, a methodology utilising a downward facing camera to analyse the ground environment in both 2D and 3D, detect safe landing sites and characterise them according to size, shape, slope and nearby obstacles. A methodology is presented showing the fusion of landing site detection from 2D imagery with a coarse Digital Elevation Map and dense 3D reconstructions using INS-aided Structure-from-Motion to improve accuracy. Results are presented from an experimental flight showing the precision/recall of landing sites in comparison to a hand-classified ground truth, and improved performance with the integration of 3D analysis from visual Structure-from-Motion.

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ID Code: 65726
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: UAV, UAS, Computer Vision, Forced Landing, Unmanned Aerial Vehicle, 3D Reconstruction, CEDM
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Please consult the authors
Deposited On: 07 Jan 2014 23:21
Last Modified: 13 Sep 2016 21:20

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