This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling


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    Title :

    Motion Planning for Autonomous Vehicles in Partially Observable Environments


    Contributors:


    Publication date :

    2023


    Size :

    1 Online-Ressource (222 p.)



    Type of media :

    Book


    Type of material :

    Electronic Resource


    Language :

    Unknown









    Robot planning in partially observable continuous domains

    Porta, Josep M. / Spaan, Matthijs T. J. / Vlassis, Nikos | BASE | 2005

    Free access