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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    Title :

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


    Contributors:


    Publication date :

    2017-06-01


    Size :

    401474 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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