摘要
针对深空探测器现有的任务规划方法在处理系统间复杂约束时存在的约束复杂度高、实时响应能力差、计算效率低等问题,提出一种新的约束简化方法和启发式连续任务规划方法。首先,在时间线规划模型中根据两两子系统间的实时状态关系定义启发式因子,并利用该因子在规划周期内的取值建立子系统间时间线临时从属关系,从而合理地降低规划过程中的约束复杂程度;然后,在规划算法中采用时间线状态扩展策略,根据时间线临时从属关系对各子系统间的状态进行横向和纵向扩展,从而实现对目标任务规划进行快速排序。仿真结果表明由启发式因子建立的时间线临时从属关系有效简化了任务规划过程中的时间约束和资源约束、提高了任务规划的效率和灵活性。
In this paper, a heuristic mission planning method is proposed to deal with the problems of high complexity, real-time response capability and low computational efficiency in the traditional mission planning algorithms for deep space explorer. Firstly, a new constraint simplification algorithm is proposed by use of a heuristic factor derived from the real-time state relationship between the two-two subsystems in the timeline planning model. By using the value of the factor, the temporary subordinate relationships of subsystems are established during the planning period, which can significantly reduce the complexity of constraints in the planning process. Secondly, the timeline state expansion strategy is adopted in the planning algorithm. These expansions are conducted in single timeline and between timelines according to the temporary subordinate relationship, thus obtaining the mission sequence quickly. The simulation results verify the effectiveness of the proposed method, and improve the efficiency and flexibility of the mission planning.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2016年第7期768-774,共7页
Journal of Astronautics
基金
国家自然科学基金(61273051)
上海航天科技创新基金(SAST2015036)
南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20151501)
关键词
深空探测
任务规划
时间线
启发式
约束简化
Mission planning
Constraint simplification
Timeline
Heuristic
Deep space exploration
