This paper presents the application of a monocular visual SLAM on a fixed-wing small Unmanned Aerial System (sUAS) capable of simultaneous estimation of aircraft pose and scene structure. The authors 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. The authors 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 1×1 km rural area at an altitude of 20-100 m. The authors 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. They compare the accuracy of the 6-DOF pose estimates to an off-the-shelf GPS aided INS over a 1.7 km trajectory. They also present output 3D reconstructions of the observed scene structure and texture that demonstrates future applications in autonomous monitoring and surveying.


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    Title :

    Large Scale Monocular Vision-Only Mapping from a Fixed-Wing sUAS


    Contributors:
    Warren, Michael (author) / McKinnon, David (author) / He, Hu (author) / Glover, Arren (author) / Shiel, Michael (author) / Upcroft, Ben (author)


    Publication date :

    2013


    Size :

    15 Seiten





    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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