This paper proposes a path finding method for two unmanned aerial vehicles with localization constraints using a modified shortest path algorithm. A beacon vehicle has GPS or other absolute positioning information, and a target vehicle has only bearing information taken relative to the beacon vehicle or known stationary landmarks. By overlaying a grid on the map and discretizing the position uncertainty, the path planning problem for two vehicles can be formulated as a dynamic programming problem and solved using a modified form of the A∗ shortest path algorithm. Edge costs are found using a factored covariance method for an Extended Kalman filter based on results available in literature. In simulation, paths found from the dynamic programming method outperform a greedy algorithm.


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    Titel :

    A grid-based path planning approach for a team of two vehicles with localization constraints


    Beteiligte:


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    401474 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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