基于约束可满足的深空探测任务规划方法研究

Research on Task Planning Problems for Deep Space Exploration Based on Constraint Satisfaction

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。

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.