Autonomous systems can perform tasks that are dangerous, monotonous, or even impossible for humans. To approach the problem of planning for Unmanned Aerial Vehicles (UAVs) we present a hierarchical method that combines a high-level planner with a low-level planner. We pose the problem of high-level planning as a Selective Traveling Salesman Problem (STSP) and select the order in which to visit our science sites. We then use a kino-dynamic path planner to create a large number of intermediate waypoints. This is a complete system that combines high and low level planning to achieve a goal. This paper demonstrates the benefits gained by adaptable high-level plans versus static and greedy plans.


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    Title :

    Adaptable mission planning for kino-dynamic systems


    Contributors:


    Publication date :

    2013-03-01


    Size :

    1849018 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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