Large scale monocular vision-only mapping from a fixed-wing sUAS


Autoria(s): Warren, Michael; McKinnon, David; He, Hu; Glover, Arren; Shiel, Michael; Upcroft, Ben
Data(s)

2014

Resumo

This paper presents the application of a monocular visual SLAMon a fixed-wing small Unmanned Aerial System (sUAS) capable of simultaneous estimation of aircraft pose and scene structure. We demonstrate the robustness of unconstrained vision alone in producing reliable pose estimates of a sUAS, at altitude. It is ultimately capable of online state estimation feedback for aircraft control and next-best-view estimation for complete map coverage without the use of additional sensors.We explore some of the challenges of visual SLAM from a sUAS including dealing with planar structure, distant scenes and noisy observations. The developed techniques are applied on vision data gathered from a fast-moving fixed-wing radio control aircraft flown over a 1×1km rural area at an altitude of 20-100m.We present both raw Structure from Motion results and a SLAM solution that includes FAB-MAP based loop-closures and graph-optimised pose. Timing information is also presented to demonstrate near online capabilities. We compare the accuracy of the 6-DOF pose estimates to an off-the-shelfGPS aided INS over a 1.7kmtrajectory.We also present output 3D reconstructions of the observed scene structure and texture that demonstrates future applications in autonomous monitoring and surveying.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/53102/

Publicador

Springer

Relação

http://eprints.qut.edu.au/53102/1/author.pdf

https://www.softconf.com/c/fsr2012/

DOI:10.1007/978-3-642-40686-7_33

Warren, Michael, McKinnon, David, He, Hu, Glover, Arren, Shiel, Michael, & Upcroft, Ben (2014) Large scale monocular vision-only mapping from a fixed-wing sUAS. In Field and Service Robotics: Results of the 8th International Conference [Springer Tracts in Advanced Robotics, Volume 92], Springer, Matsushima, Japan, pp. 495-509.

Direitos

Copyright 2012 [please consult the author]

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080101 Adaptive Agents and Intelligent Robotics #Computer Vision #UAV #Visual Odometry #Pose Estimation #Structure from Motion
Tipo

Conference Paper