| 摘要: |
| 基于传统的CSP算法不能充分体现规划过程的特点，讨论了如何将规划中的动作关系映射到CSP结构中，并据此提出了一种以动作为中心的启发式变量选择策略；分析验证了该方法能够显著降低传统CSP变量搜索策略的时间复杂度，同时对于约束编码的规划问题具有一般适用性。仿真实验表明，本文提出的方法减少了约束处理中的冗余操作，有效提高了问题的求解效率，为工程应用奠定了基础。 |
| 关键词: 规划 约束可满足 变量选取 动作指向 |
| DOI：10.15982/j.issn.2095-7777.2018.6.008 |
| 分类号:TP18 |
| 基金项目:基础科研计划资助项目（JCKY2016602C018） |
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| Research on Task Planning Problems for Deep Space Exploration Based on Constraint Satisfaction |
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JIANG Xiao1,2, XU Rui1,2, ZHU Shengying1,2
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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
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| Abstract: |
| The ordinary CSP algorithms cannot reflect the characteristics of the task planning progress. How the action rules in task planning for deep space exploration can be mapped into the constraint satisfaction problems is discussed. Based on the conclusion,an action directed constraint is proposed to guide the variable selection procedure in constraint satisfaction problems. Through theoretical analysis,the proposed technology can be used in constraint-programmed planning problem. The simulation experiments show that the algorithm with action guided constraint can effectively reduce the number of constraint checks during the planning procedure and has a better performance on total running time over the standard version. It lays the foundation for the application of the project. |
| Key words: planning constraint satisfaction variable selection action-oriented |
