This paper presents a navigation system that enables small-scale unmanned aerial vehicles to navigate autonomously in foliage environment without GPS using a 2D laser range finder. The navigation framework consists of real-time onboard motion estimation and trajectory smoothing using pose graph optimization, real-time dual layer control. In particular, onboard real-time motion estimation is achieved in a Kalman filter, fusing the planar velocity measurement from scan matching of laser range finder and the acceleration measurement of inertial measurement unit. The trajectory histories from the real-time autonomous navigation together with the observed features are fed into a pose-graph optimization framework. Poses in a sliding window are optimized using GraphSLAM technique. The inner loop of a quadrotor is stabilized using a commercial autopilot while the outer loop control is implemented using robust perfect tracking. The performance of the navigation system is demonstrated on the successful autonomous navigation of a small-scale UAV in forest. Consistent mapping of the environment in indoor and outdoor scenarios are achieved by projecting all the scan measurement on the post-optimized trajectory with GraphSLAM.


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    Titel :

    Autonomous navigation of UAV in forest


    Beteiligte:
    Cui, Jin Qiang (Autor:in) / Lai, Shupeng (Autor:in) / Dong, Xiangxu (Autor:in) / Liu, Peidong (Autor:in) / Chen, Ben M. (Autor:in) / Lee, Tong H. (Autor:in)


    Erscheinungsdatum :

    2014-05-01


    Format / Umfang :

    2538599 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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