In this work, we consider the optimal path of a fixed-wing unmanned aerial vehicle (UAV) tracking a mobile surface target. One of the limitations of fixed-wing UAVs in tracking mobile targets is the lack of hovering capability when the target moves much slower than the minimum UAV speed, requiring the UAV maintain an orbit about the target. In this paper, we propose a method to find the optimal policy for fixed-wing UAVs to minimize the location uncertainty of a mobile target. using a grid-based Markov Decisive Process (MDP), we process a policy iteration algorithm offline to find the optimal UAV path in a discretized state space. Based on the offline optimal policy, we generate a finer grid MDP for the region of interest to efficiently process an online policy iteration to find in real-time the optimal trajectory for a UAV. We validate the proposed algorithm using computer simulations. Comparing the simulation results with other methods, we show that the proposed method has up to 13% decrease in error uncertainty than ones resulted using conventional methods.


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    Title :

    Optimal Path Planning of a Target Following Fixed Wing UAV Using Sequential Decision Processes


    Contributors:
    S. S. Baek (author) / H. Kwon (author) / J. A. Yoder (author) / D. Pack (author)

    Publication date :

    2013


    Size :

    8 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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