Coordinated dynamic mission planning scheme for intelligent multi-agent systems

Coordinated dynamic mission planning scheme for intelligent multi-agent systems
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智能多智能体系统协调动态任务规划方案

DOI:
10.1007/s11771-012-1392-8
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发表时间:
2012-11
期刊:
中南大学学报(英文版)
影响因子:
--
通讯作者:
Kuo-chi Lin
Kuo-chi Lin
中科院分区:
其他
文献类型:
--
作者:
Jun Peng;Mengfei Wen;Guoqi Xie;Xiaoyong Zhang;Kuo-chi Lin

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使命规划在多智能代理系统,如多个无人驾驶航空器和多处理器系统的领域进行了深入研究。然而,由于系统的复杂性、执行顺序的约束和动态环境的不确定性,它仍然面临着挑战。针对这一问题,提出了一种基于加权与或树和AOE网络的协同动态使命规划方法。该方案将使命分解为时间约束加权与或树,并将其转化为AOE网络进行使命规划。在此基础上,设计了一种动态规划算法,采用任务分包和动态再分解的方法协调冲突。该方案通过实现实时动态重规划,降低了任务复杂度和执行时间。仿真结果证明了该方法的有效性。
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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