Self-reconfiguration Strategies for Space-distributed Spacecraft

Liu, Tianle and Wang, Zhixiang and Zhang, Yongwei and Wang, Ziwei and Liu, Zihao and Zhang, Yizhai and Huang, Panfeng (2024) Self-reconfiguration Strategies for Space-distributed Spacecraft. In: 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) :. IEEE, pp. 9879-9884. ISBN 9798350377712

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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.