Enabling aircraft emergency landings using active visual site detection


Autoria(s): Warren, Michael; Mejias, Luis; Yang, Xilin; Arain, Bilal; Gonzalez, Felipe; Upcroft, Ben
Contribuinte(s)

Corke, Peter

Mejias, Luis

Roberts, Jonathan

Data(s)

11/12/2013

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/65726/

Relação

http://eprints.qut.edu.au/65726/1/author.pdf

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.

Direitos

Copyright 2013 Please consult the authors

Fonte

Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080101 Adaptive Agents and Intelligent Robotics #UAV #UAS #Computer Vision #Forced Landing #Unmanned Aerial Vehicle #3D Reconstruction #CEDM
Tipo

Conference Paper