基于数据与压缩率预测的空间机器人集群中心节点选择策略

doi:10.7523/j.ucas.2023.007

中国科学院大学学报 ›› 2024, Vol. 41 ›› Issue (5): 695-704.DOI: 10.7523/j.ucas.2023.007

• 电子信息与计算机科学 • 上一篇

基于数据与压缩率预测的空间机器人集群中心节点选择策略

杨晅, 陈宏宇

中国科学院微小卫星创新研究院, 上海 201203;
上海科技大学, 上海 201210;
中国科学院大学, 北京 100049

收稿日期:2022-10-24 修回日期:2023-02-07 发布日期:2023-03-21
通讯作者: 陈宏宇,E-mail:chenhy@microsate.com

Central node selection strategy of spatial robot cluster based on data and compression ratio prediction

YANG Xuan, CHEN Hongyu

Innovation Academy for Microsatellites, Chinese Academy of Sciences, Shanghai 201203, China;
ShanghaiTech University, Shanghai 201210, China;
University of Chinese Academy of Sciences, Beijing 100049, China

Received:2022-10-24 Revised:2023-02-07 Published:2023-03-21

摘要/Abstract

摘要： 近年来，空间机器人集群方式的在轨服务技术受到各航天大国的重视。空间机器人集群对目标航天器进行在轨服务时，要将收集的目标信息传输至中枢卫星，如何均衡集群中每个节点的通信功耗是一个重要的研究问题。针对空间机器人集群与数据中枢卫星之间的通信功率最优问题，提出一种基于数据及其压缩率预测的空间机器人集群中心节点选择算法(DCP)。由于集群通信中的通信功耗主要与通信距离和通信时长 (数据量) 有关，可以基于集群的运动轨迹预测未来时刻的数据和压缩率，从而选择最优的集群中心节点，构建通信链路。在实验仿真中，与固定中心算法、度中心性算法、介数中心性算法以及接近中心性算法相比，DCP算法可以有效降低集群通信功耗，并且与实际的最优结果相比误差小于3%。

关键词: 空间机器人, 空间机器人集群, 集群通信, 中心节点选取

Abstract: In recent years, the in-orbit service technology of space robot clusters has attracted the attention of various space powers. When the space robot cluster serves the target spacecraft in orbit, the collected target information needs to be transmitted to the central satellite. How to balance the communication power consumption of each node in the cluster is an important research problem. Aiming at the problem of optimal communication power between the space robot cluster and the data hub satellite, a central node selection algorithm (data and data compression ratio prediction，DCP) based on data and compression ratio prediction was proposed in this paper. Since the communication power consumption in the cluster communication is mainly related to the communication distance and communication duration (data volume), the data and compression rate at future times can be predicted based on the movement trajectory of the cluster, thus selecting the optimal central node of the cluster and constructing the communication link. In the experimental simulation, compared to a fixed point, degree centrality, betweenness centrality, and closeness centrality, DCP algorithm can effectively reduce the power consumption of cluster communication, and the error is less than 3% compared with the actual optimal result.

Key words: space robots, space robot clusters, cluster communication, center node selection

中图分类号:

TN927+.2

杨晅, 陈宏宇. 基于数据与压缩率预测的空间机器人集群中心节点选择策略[J]. 中国科学院大学学报, 2024, 41(5): 695-704.

YANG Xuan, CHEN Hongyu. Central node selection strategy of spatial robot cluster based on data and compression ratio prediction[J]. Journal of University of Chinese Academy of Sciences, 2024, 41(5): 695-704.

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基于数据与压缩率预测的空间机器人集群中心节点选择策略

Central node selection strategy of spatial robot cluster based on data and compression ratio prediction

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