The characteristics of unmanned vehicle makes it be used widely in industrial production, space exploration and other fields and unmanned vehicle navigation positioning technology is the most basic aspects. This paper discusses the integrated positioning technology of unmanned vehicle which combines vision sensor with the dead reckoning to achieve precise positioning of the vehicles. By introducing the normal estimated of point cloud, the expected plane feature of point cloud data can be extracted with RANSAC well, which is done with Point Cloud Library (PCL). The effect of unmanned vehicle positioning is also discussed with the plane feature. The corresponding program is applied in the P3-AT Pioneer Robot for validation.


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    Title :

    Point Cloud Feature Extraction Based Integrated Positioning Method for Unmanned Vehicle



    Published in:

    Publication date :

    2014-06-30


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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