Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866918206641274880 |
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| author | Yang, Juntang Ben-Larbi, Mohamed Khalil |
| author_facet | Yang, Juntang Ben-Larbi, Mohamed Khalil |
| contents | This paper implements deep reinforcement learning (DRL) for spacecraft reorientation control with a single pointing keep-out zone. The Soft Actor-Critic (SAC) algorithm is adopted to handle continuous state and action space. A new state representation is designed to explicitly include a compact representation of the attitude constraint zone. The reward function is formulated to achieve the control objective while enforcing the attitude constraint. A curriculum learning approach is used for the agent training. Simulation results demonstrate the effectiveness of the proposed DRL-based method for spacecraft pointing-constrained attitude control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13746 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint Yang, Juntang Ben-Larbi, Mohamed Khalil Systems and Control Artificial Intelligence Machine Learning This paper implements deep reinforcement learning (DRL) for spacecraft reorientation control with a single pointing keep-out zone. The Soft Actor-Critic (SAC) algorithm is adopted to handle continuous state and action space. A new state representation is designed to explicitly include a compact representation of the attitude constraint zone. The reward function is formulated to achieve the control objective while enforcing the attitude constraint. A curriculum learning approach is used for the agent training. Simulation results demonstrate the effectiveness of the proposed DRL-based method for spacecraft pointing-constrained attitude control. |
| title | Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint |
| topic | Systems and Control Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2511.13746 |