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基于状态转移图的启发式深空探测器任务规划方法
金颢1,2, 徐瑞1,2, 崔平远1,2, 朱圣英1,2
1.北京理工大学 深空探测技术研究所, 北京 100081;2.深空自主导航与控制工业和信息化部重点实验室, 北京 100081
摘要:
针对深空探测器复杂系统并行及约束耦合等特点,在时间线描述框架的基础上,引入了状态转移图结构。通过分析探测器任务规划中的耦合约束关系,设计了转移图代价计算方法,并提出了基于状态转移图的启发式任务规划算法。利用转移图设计启发式对无关节点进行剪枝,削减了搜索空间,加速了搜索过程。数值仿真结果表明,该算法能够有效减少不必要的规划步数,提高任务规划的效率。
关键词:  任务规划;启发式搜索;状态转移图
DOI:10.15982/j.issn.2095-7777.2019.04.008
分类号:TP18
基金项目:民用航天资助项目(MYHT201705)
Heuristic Search Based on State Transition Graphs for Deep Space Task Planning
JIN Hao1,2, XU Rui1,2, CUI Pingyuan1,2, ZHU Shengying1,2
1.Institute of Deep Space Exploration, Beijing Institute of Technology, Beijing 100081, China;2.Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, Beijing 100081, China
Abstract:
In view of the complex system and coupling operation constraints of deep space probes,state transition graphs are defined based on the timeline knowledge representation. With the analysis of involved constraints in task planning,the computation procedure of cost estimate for state transition is designed. In addition,the state transition graph based heuristic planning algorithm is proposed and is able to prune irrelevant search space,and accelerate the searching process. Simulation results indicate that the algorithm can reduce unnecessary planning steps and make certain improvements in planning efficiency.
Key words:  task planning;heuristic search;state transition graph