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基于扩展状态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:
面对深空探测过程中的不确定性,探测器需要利用任务规划技术实现自主控制。针对深空探测器任务规划中复杂系统功能及耦合操作约束,在状态知识框架的基础上,引入了扩展状态的概念。通过分析探测器任务规划中的约束关系,提出了基于扩展状态的任务规划算法。利用扩展状态结构特点削减了搜索空间,优化了搜索过程,提高了规划搜索的速度。数值仿真结果表明,该算法能够缩减近半的规划步数,加速问题求解进程,提高任务规划的效率。
关键词:  任务规划;扩展状态;规划算法
DOI:10.15982/j.issn.2095-7777.2018.06.010
分类号:TP18
基金项目:基础科研计划资助项目(JCKY2016602C018)
Mission Planning Approach Based on Extensible States for Deep Space Probes
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:
Due to the uncertainty in deep space exploration,mission planning technology is required for deep space probes to realize autonomous control. In view of the complex function and coupling operation constraints of deep space mission planning,the extensible states are defined based on the state knowledge framework. Based on the analysis of involved constraints in mission planning,the extensible state based planning algorithm is proposed. And the designed structure of extensible states is able to prune irrelevant search space,accelerate the searching process and improve the planning efficiency. The comprehensive experiments are carried out and the computational results indicate that our algorithm can reduce nearly half of the planning steps,accelerate the process of problem solving,and improve the efficiency of mission planning
Key words:  mission planning;extensible states;planning algorithm