This paper presents a vehicle navigation system that is capable of achieving sub-meter GPS-denied navigation accuracy in large-scale urban environments, using pre-mapped visual landmarks. Our navigation system tightly couples IMU data with local feature track measurements, and fuses each observation of a pre-mapped visual landmark as a single global measurement. This approach propagates precise 3D global pose estimates for longer periods. Our mapping pipeline leverages a dual-layer architecture to construct high-quality pre-mapped visual landmarks in real time. Experimental results demonstrate that our approach provides sub-meter GPS-denied navigation solutions in large-scale urban scenarios.


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    Title :

    Sub-meter vehicle navigation using efficient pre-mapped visual landmarks


    Contributors:


    Publication date :

    2016-11-01


    Size :

    2590672 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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