Localisation via the fusion of spatially referring natural language statements is considered here. The contribution lies in the underlying problem formulation and a robust modelling framework. Random-set-based estimation is the underlying mathematical formalism. Each statement generates a generalised likelihood function. A Bayesian filter is outlined that takes a sequence of likelihoods generated by multiple statements. The idea is to recursively build a map over the state space that can be used to infer the state.


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    Titel :

    Fusion of Spatially Referring Natural Language Statements with Random Set Theoretic Likelihoods


    Beteiligte:
    Bishop, A. N. (Autor:in) / Ristic, B. (Autor:in)


    Erscheinungsdatum :

    01.04.2013


    Format / Umfang :

    6302191 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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