Typically, a human agent or a robotic device may sweep a suspected minefield in a systematic up and down pattern. In this paper we consider alternative search patterns which take advantage of a priori knowledge of the minefield. In our previous work (1998), a gradient based search algorithm has been designed and shown to be an effective search strategy using simulations on hypothetical minefield data. This paper considers a suite of fast search heuristics based on a hierarchical two level approach, and evaluates these algorithms with the realistic sensory data, specifically the electromagnetic sensory data from DARPA. The heuristics considered include a hierarchical version of our gradient based algorithm, a nearest neighbor type greedy heuristic, and a heuristic which is inspired from an approximate solution of the travelling salesman problem.


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    Titel :

    Autonomous search for mines. II. Hierarchical search using sensory data


    Beteiligte:
    Cao, Yonghuan (Autor:in) / Gelenbe, E. (Autor:in)


    Erscheinungsdatum :

    1998


    Format / Umfang :

    11 Seiten, 16 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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