We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultra-reliability, high-speed operation, complex inter-vehicle interaction, parking in large unstructured lots, and constrained maneuvers. Our approach combines a model-predictive trajectory generation algorithm for computing dynamically-feasible actions with two higher-level planners for generating long range plans in both on-road and unstructured areas of the environment. In this Part II of a two-part paper, we describe the unstructured planning component of this system used for navigating through parking lots and recovering from anomalous on-road scenarios. We provide examples and results from "Boss", an autonomous SUV that has driven itself over 3000 kilometers and competed in, and won, the Urban Challenge.


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    Title :

    Motion planning in urban environments. Part II


    Contributors:
    Ferguson, D. (author) / Howard, T.M. (author) / Likhachev, M. (author)


    Publication date :

    2008


    Size :

    7 Seiten, 21 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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