This paper describes an algorithm that generates vehicle task assignments for autonomous uninhabited air vehicles in cooperative missions. The algorithm uses a state- space best-first search of a tree that incorporates all of the constraints of the assignment problem. Using this algorithm a feasible solution is generated immediately, that monotonically improves and eventually converges to the optimal solution. Using Monte Carlo simulations the performance of the search algorithm is analyzed and compared to the desirable assignment algorithm attributes. It is shown that the proposed deterministic search method can be implemented for given run times, providing good feasible solutions.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    State-Space Search for Improved Autonomous UAVs Assignment Algorithm


    Contributors:
    S. J. Rasmussen (author) / T. Shima (author) / J. W. Mitchell (author) / A. G. Sparks (author) / P. Chandler (author)

    Publication date :

    2004


    Size :

    7 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English






    Simulation Framework for Autonomous Search and Rescue UAVs

    Lemmens, Yves / Hegde, Anoosh / Teirlinck, Casper et al. | AIAA | 2022


    Simulation Framework for Autonomous Search and Rescue UAVs

    Lemmens, Yves / Hegde, Anoosh / Teirlinck, Casper et al. | TIBKAT | 2022


    UAVs’ autonomous collision avoidance in urban space*

    Wei, Ruixuan / Zhang, Qirui / Xu, Zhuofan et al. | IEEE | 2018