Abstract
Mission planning was thoroughly studied in the areas of multiple intelligent agent systems, such as multiple unmanned air vehicles, and multiple processor systems. However, it still faces challenges due to the system complexity, the execution order constraints, and the dynamic environment uncertainty. To address it, a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network. In the scheme, the mission is decomposed into a time-constraint weighted AND/OR tree, which is converted into an AOE-Network for mission planning. Then, a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts. The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning. The simulation proves the effectiveness of this approach.
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