论文:2021,Vol:39,Issue(6):1222-1232
引用本文:
张震, 方群, 宋金丰, 张修玮, 朱战霞. 基于协同粒子群算法的航天器集群动态路径规划算法研究[J]. 西北工业大学学报
ZHANG Zhen, FANG Qun, SONG Jinfeng, ZHANG Xiuwei, ZHU Zhanxia. Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm[J]. Northwestern polytechnical university

基于协同粒子群算法的航天器集群动态路径规划算法研究
张震, 方群, 宋金丰, 张修玮, 朱战霞
西北工业大学 航天飞行动力学技术重点实验室, 陕西 西安 710072
摘要:
针对航天器集群在考虑障碍物规避前提下到达动态目标点的路径规划问题中,传统粒子群算法的搜索半径固定,会导致航天器在接近目标点时难以寻找到较优值的问题,将各成员航天器的轨道动力学问题转换为一种考虑约束下的最优化问题,提出了一种基于协同粒子群算法(CPSO)的路径规划方法:提出一种随着航天器与目标点之间距离变化而改变搜索半径的动态半径搜索法,并以此对CPSO算法进行改进。改进的CPSO算法通过动态搜索半径自主寻找当前时刻各成员航天器的最优路径,从而得到三维空间中航天器集群动态路径规划问题的最优解。仿真结果表明,采用改进的CPSO算法不仅可以得到航天器集群动态路径规划问题的最优解,还可以大大减少其路径规划中的燃料消耗量,提高各成员航天器路径的稳定性。
关键词:    航天器集群    动态路径规划    协同粒子群算法    动态搜索半径   
Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm
ZHANG Zhen, FANG Qun, SONG Jinfeng, ZHANG Xiuwei, ZHU Zhanxia
Key Laboratory of Aerospace Flight Dynamics Technology, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
In order to solve the problem of path planning for the spacecraft cluster to reach the dynamic target point under the premise of considering obstacle avoidance. In view of the fixed search radius, it will be difficult for the spacecraft to find a better value when it is close to the target point. This paper converts the orbital dynamics of each member spacecraft into an optimization problem considering constraints, and proposes an improved CPSO algorithm based on coordination. The path planning method of the traditional particle swarm optimization (CPSO):The dynamic radius search method that changes the search radius by changing the distance between them, and improves the CPSO algorithm based on this. The improved CPSO algorithm autonomously finds the optimal path of each member spacecraft at the current moment through the dynamic search radius, thereby obtaining the optimal solution for the dynamic path planning of the spacecraft cluster in three-dimensional space. The simulation results show that the use of the improved CPSO algorithm can not only obtain the optimal solution to the spacecraft cluster dynamic path planning problem, but also greatly reduce the fuel consumption in its path planning and improve the path stability of each member spacecraft.
Key words:    spacecraft cluster    dynamic path planning    collaborative particle swarm optimization    dynamic search radius   
收稿日期: 2021-04-15     修回日期:
DOI: 10.1051/jnwpu/20213961222
通讯作者: 方群(1960-),女,西北工业大学教授,主要从事飞行力学与控制研究。e-mail:qfang@nwpu.edu.cn     Email:qfang@nwpu.edu.cn
作者简介: 张震(1997-),西北工业大学硕士研究生,主要从事空间避障轨迹规划、航天器及空间碎片群轨道预测等研究。
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参考文献:
[1] DAS P K, BEHERA H S, PANIGRAHI B K. A hybridization of an improved particle swarm optimization and gravitational search algorithm for multi-robot path planning[J]. Swarm & Evolutionary Computation, 2016,28:14-28
[2] NOUYAN S, CAMPO A, DORIGO M. Path formation in a robot swarm[J]. Swarm Intelligence, 2008, 2(1):1-23
[3] SPERATI V, TRIANNI V, NOLFI S. Evolution of self-organised path formation in a swarm of robots[C]//International Conference on Swarm Intelligence, 2010
[4] MCINNES C R. Autonomous path planning for on-orbit servicing vehicles[J]. Journal of the British Interplanetary Society, 2000, 53(1/2):26-38
[5] LAVALLE S M, KUFFNER JR J J. Randomized kinodynamic planning[J]. The International Journal of Robotics Research, 2001, 20(5):378-400
[6] FRAZZOLI Emilio. Quasi-random algorithms for real-time spacecraft motion planning and coordination[J]. Acta Astronautic. 2003,53(4/5/6/7/8/9/10):485-494
[7] FERON E, DAHLEH M, FRAZZOLI E, et al. A randomized attitude slew planning algorithm for autonomous spacecraft[C]//AIAA Guidance, Navigation, and Control Conference and Exhibit, California, 2012
[8] CHENG P, FRAZZOLI E, LAVALLE S M. Improving the performance of sampling-based planners by using a symmetry-exploiting gap reduction algorithm[C]//IEEE International Conference on Robotics and Automation, 2004
[9] WANG P K C, HADAEGH F Y. Minimum-fuel formation reconfiguration of multiple free-flying spacecraft[J]. Journal of Astronautics Science, 1999, 47(1):77-102
[10] 曹静, 沈红新, 李恒年. 多星编队构型重构全局优化策略——第七届全国空间轨道设计竞赛乙题解法[J]. 力学与实践, 2016, 38(6):697-704 CAO Jing, SHEN Hongxin, LI Hengnian. Global optimization strategy for reconfiguration of multi-satellite formations——solution to the second question of the 7th national space orbit design competition[J]. Mechanics in Engineering, 2016, 38(6):697-704(in Chinese)
[11] 黄海滨. 卫星编队飞行自主队形重构方法研究[D]. 哈尔滨:哈尔滨工业大学, 2011 HUANG Haibin. Research on the method of autonomous formation reconstruction of satellite formation flying[D]. Harbin:Harbin Institute of Technology, 2011(in Chinese)
[12] NASROLLAHY A Z, JAVADI H H S. Using particle swarm optimization for robot path planning in dynamic environments with moving obstacles and target[C]//European Symposium on Computer Modeling and Simulation, Athens, 2009
[13] 张彬. 基于粒子群算法的群体机器人围捕行为的研究[D]. 兰州:兰州理工大学, 2013 ZHANG Bin. Research on hunting behavior of group robots based on particle swarm optimization[D]. Lanzhou:Lanzhou University of Technology, 2013(in Chinese)
[14] 谢竟. 对抗环境中多机器人群体博弈与协调控制研究[D]. 南昌:华东交通大学, 2013 XIE Jing. Research on multi-robot group game and coordinated control in confrontation environment[D]. Nanchang:East China Jiaotong University, 2013(in Chinese)
[15] HOWARD D Curtis. 轨道力学[M]. 周建华,译. 北京:科学出版社,2019 HOWARD D Curtis. Orbital mechanics[M]. ZHOU Jianhua, Trans. Beijing:Science Press, 2019
[16] 王兆奎. 分布式卫星动力学建模与控制研究[D]. 长沙:国防科技大学, 2006 WANG Zhaokui. Research on distributed satellite dynamics modeling and control[D]. Changsha:National University of Defense Technology, 2006(in Chinese)
[17] 王融, 熊智, 刘建业. 基于逐次多脉冲的相对制导算法研究[J]. 自动化与仪器仪表, 2018(1):4-8 WANG Rong, XIONG Zhi, LIU Jianye. Research on relative guidance algorithm based on successive multi-pulse[J]. Automation and Instrumentation, 2018(1):4-8(in Chinese)
[18] 方群, 李新国, 朱战霞, 等. 航天飞行动力学[M]. 西安:西北工业大学出版社, 2015 FANG Qun, LI Xinguo, ZHU Zhanxia, et al. Aerospace flight dynamics[M]. Xi'an:Northwestern Polytechnical University Press, 2015(in Chinese)
[19] WANG Z, HIRATA Y, KOSUGE K. Dynamic object closure by multiple mobile robots and random caging formation testing[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, 2006
[20] WAN W, SUN C, YUAN J. The caging configuration design and optimization for planar moving objects using multi-fingered mechanism[J]. Advanced Robotics, 2019, 33(18):925-943