Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm
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. Th...
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Format: | Article |
Language: | zho |
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EDP Sciences
2021-12-01
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Series: | Xibei Gongye Daxue Xuebao |
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Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2021/06/jnwpu2021396p1222/jnwpu2021396p1222.html |
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author | Zhang Zhen Fang Qun Song Jinfeng Zhang Xiuwei Zhu Zhanxia |
author_facet | Zhang Zhen Fang Qun Song Jinfeng Zhang Xiuwei Zhu Zhanxia |
author_sort | Zhang Zhen |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-11T14:09:54Z |
format | Article |
id | doaj.art-1cd3ac6a324247fe990bd2c145d90de1 |
institution | Directory Open Access Journal |
issn | 1000-2758 2609-7125 |
language | zho |
last_indexed | 2024-03-11T14:09:54Z |
publishDate | 2021-12-01 |
publisher | EDP Sciences |
record_format | Article |
series | Xibei Gongye Daxue Xuebao |
spelling | doaj.art-1cd3ac6a324247fe990bd2c145d90de12023-11-02T00:19:23ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252021-12-013961222123210.1051/jnwpu/20213961222jnwpu2021396p1222Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithmZhang ZhenFang QunSong JinfengZhang XiuweiZhu ZhanxiaIn 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.https://www.jnwpu.org/articles/jnwpu/full_html/2021/06/jnwpu2021396p1222/jnwpu2021396p1222.htmlspacecraft clusterdynamic path planningcollaborative particle swarm optimizationdynamic search radius |
spellingShingle | 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 Xibei Gongye Daxue Xuebao spacecraft cluster dynamic path planning collaborative particle swarm optimization dynamic search radius |
title | Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm |
title_full | Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm |
title_fullStr | Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm |
title_full_unstemmed | Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm |
title_short | Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm |
title_sort | research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm |
topic | spacecraft cluster dynamic path planning collaborative particle swarm optimization dynamic search radius |
url | https://www.jnwpu.org/articles/jnwpu/full_html/2021/06/jnwpu2021396p1222/jnwpu2021396p1222.html |
work_keys_str_mv | AT zhangzhen researchondynamicpathplanningalgorithmofspacecraftclusterbasedoncooperativeparticleswarmalgorithm AT fangqun researchondynamicpathplanningalgorithmofspacecraftclusterbasedoncooperativeparticleswarmalgorithm AT songjinfeng researchondynamicpathplanningalgorithmofspacecraftclusterbasedoncooperativeparticleswarmalgorithm AT zhangxiuwei researchondynamicpathplanningalgorithmofspacecraftclusterbasedoncooperativeparticleswarmalgorithm AT zhuzhanxia researchondynamicpathplanningalgorithmofspacecraftclusterbasedoncooperativeparticleswarmalgorithm |