多节点探测器附着任务分层约束图模型及重规划算法  

Layered constraint graph model and re-planning algorithm for landing of probe with multiple nodes

作　　者：杨和星 赵清杰[1] 王鑫 付康 YANG He-xing;ZHAO Qing-jiey;WANG Xin;FU Kang(School of Computer Science and Technology,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学计算机学院,北京100081

出　　处：《控制与决策》2025年第2期626-634,共9页Control and Decision

基　　金：国家重点研发计划项目(2019YFA0706500)。

摘　　要：针对多节点深空探测器附着小天体过程中的任务重规划问题研究规划约束模型和重规划算法.基于多节点协同工作机制和复杂时间约束形式,定义时间约束与系统图表示,构建描述探测器系统的分层约束图并提出多节点探测器附着任务分层验证及搜索重规划算法.算法结合二分思想和动态规划思想,具体包括分层时延满足验证机制和分层约束搜索算法两部分.通过对约束进行不同粒度的分级存储,建立突发约束的时延满足验证机制.对于整体时延无法满足全部约束的情况,基于约束点的分级匹配方法设计多粒度约束搜索算法.仿真实验表明,所提出算法能够快速生成时间约束损失代价最小的重规划结果,以满足深空探测场景下的实时自主决策需求.To address the challenge of mission re-planning when a deep space probe with multiple nodes landing on small celestial bodies,a planning constraint model and a re-planning algorithm are studied.Based on the multiple nodes collaborative working mechanism and complex time constraint forms,the graph representation of system and time constraints are defined,and a layered constraint graph is constructed to describe the deep space probe system.The proposed algorithm combines the idea of binary and dynamic programming,including a layered delay satisfaction verification mechanism and a layered constraint search algorithm.A delay satisfaction verification mechanism for burst constraints is established by hierarchical storage of constraints with different granularity.For the scenarios where the overall delay cannot meet all constraints,a multi granularity constraint search algorithm is proposed based on the hierarchical matching of constraints.Simulation experiments show that the proposed algorithm can quickly generate a re-planning result with minimal time constraint loss cost to meet the real-time autonomous decision-making requirements for deep space explorations.

关 键 词：多节点探测器 分层约束图 任务重规划 小天体附着 规划约束模型 协同工作 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]