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Self-reconfiguration Strategies for Space-distributed Spacecraft

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Self-reconfiguration Strategies for Space-distributed Spacecraft. / Liu, Tianle; Wang, Zhixiang; Zhang, Yongwei et al.
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2024. p. 9879-9884.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Liu, T, Wang, Z, Zhang, Y, Wang, Z, Liu, Z, Zhang, Y & Huang, P 2024, Self-reconfiguration Strategies for Space-distributed Spacecraft. in 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, pp. 9879-9884. https://doi.org/10.1109/iros58592.2024.10802829

APA

Liu, T., Wang, Z., Zhang, Y., Wang, Z., Liu, Z., Zhang, Y., & Huang, P. (2024). Self-reconfiguration Strategies for Space-distributed Spacecraft. In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 9879-9884). IEEE. https://doi.org/10.1109/iros58592.2024.10802829

Vancouver

Liu T, Wang Z, Zhang Y, Wang Z, Liu Z, Zhang Y et al. Self-reconfiguration Strategies for Space-distributed Spacecraft. In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE. 2024. p. 9879-9884 Epub 2024 Oct 14. doi: 10.1109/iros58592.2024.10802829

Author

Liu, Tianle ; Wang, Zhixiang ; Zhang, Yongwei et al. / Self-reconfiguration Strategies for Space-distributed Spacecraft. 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2024. pp. 9879-9884

Bibtex

@inproceedings{fd9198f7d50f438892cbfddab184c63c,
title = "Self-reconfiguration Strategies for Space-distributed Spacecraft",
abstract = "This paper proposes a distributed on-orbit spacecraft assembly algorithm, where future spacecraft can assemble modules with different functions on orbit to form a spacecraft structure with specific functions. This form of spacecraft organization has the advantages of reconfigurability, fast mission response and easy maintenance. Reasonable and efficient on-orbit self-reconfiguration algorithms play a crucial role in realizing the benefits of distributed spacecraft. This paper adopts the framework of imitation learning combined with reinforcement learning for strategy learning of module handling order. A robot arm motion algorithm is then designed to execute the handling sequence. We achieve the self-reconfiguration handling task by creating a map on the surface of the module, completing the path point planning of the robotic arm using A*. The joint planning of the robotic arm is then accomplished through forward and reverse kinematics. Finally, the results are presented in Unity3D.",
author = "Tianle Liu and Zhixiang Wang and Yongwei Zhang and Ziwei Wang and Zihao Liu and Yizhai Zhang and Panfeng Huang",
year = "2024",
month = dec,
day = "25",
doi = "10.1109/iros58592.2024.10802829",
language = "English",
isbn = "9798350377712",
pages = "9879--9884",
booktitle = "2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Self-reconfiguration Strategies for Space-distributed Spacecraft

AU - Liu, Tianle

AU - Wang, Zhixiang

AU - Zhang, Yongwei

AU - Wang, Ziwei

AU - Liu, Zihao

AU - Zhang, Yizhai

AU - Huang, Panfeng

PY - 2024/12/25

Y1 - 2024/12/25

N2 - This paper proposes a distributed on-orbit spacecraft assembly algorithm, where future spacecraft can assemble modules with different functions on orbit to form a spacecraft structure with specific functions. This form of spacecraft organization has the advantages of reconfigurability, fast mission response and easy maintenance. Reasonable and efficient on-orbit self-reconfiguration algorithms play a crucial role in realizing the benefits of distributed spacecraft. This paper adopts the framework of imitation learning combined with reinforcement learning for strategy learning of module handling order. A robot arm motion algorithm is then designed to execute the handling sequence. We achieve the self-reconfiguration handling task by creating a map on the surface of the module, completing the path point planning of the robotic arm using A*. The joint planning of the robotic arm is then accomplished through forward and reverse kinematics. Finally, the results are presented in Unity3D.

AB - This paper proposes a distributed on-orbit spacecraft assembly algorithm, where future spacecraft can assemble modules with different functions on orbit to form a spacecraft structure with specific functions. This form of spacecraft organization has the advantages of reconfigurability, fast mission response and easy maintenance. Reasonable and efficient on-orbit self-reconfiguration algorithms play a crucial role in realizing the benefits of distributed spacecraft. This paper adopts the framework of imitation learning combined with reinforcement learning for strategy learning of module handling order. A robot arm motion algorithm is then designed to execute the handling sequence. We achieve the self-reconfiguration handling task by creating a map on the surface of the module, completing the path point planning of the robotic arm using A*. The joint planning of the robotic arm is then accomplished through forward and reverse kinematics. Finally, the results are presented in Unity3D.

U2 - 10.1109/iros58592.2024.10802829

DO - 10.1109/iros58592.2024.10802829

M3 - Conference contribution/Paper

SN - 9798350377712

SP - 9879

EP - 9884

BT - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

PB - IEEE

ER -