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- W4288709729 abstract "For the decision-making of on-orbit service with multiple geosynchronous earth orbit targets, an offline and online combined intelligent decision-making method is proposed based on reinforcement learning. Firstly, the decision-making problem is given and formulated. Then, considering the computational complexity of online decision-making, this work proposed an offline and online combined intelligent decision-making framework. A cost function related to the fuel consumption and rendezvous time is constructed offline for one spacecraft serving one target. And a RBF neural network-based method is proposed to approximate and fit the offline calculated data. For the on-orbit real-time decision-making problem, a multi-target decision-making cost function is constructed, and a low-complexity and intelligent decision-making method is proposed based on reinforcement learning to allocate the proper spacecrafts to serve the multiple targets. Simulation results show that the proposed method can achieve fast and accurate online decision-making for the service of geosynchronous earth orbit targets." @default.
- W4288709729 created "2022-07-30" @default.
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- W4288709729 date "2022-07-29" @default.
- W4288709729 modified "2023-09-26" @default.
- W4288709729 title "Intelligent Decision-Making Method for On-Orbit Service with Multiple Geosynchronous Earth Orbit Targets Based on Reinforcement Learning" @default.
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- W4288709729 doi "https://doi.org/10.1007/978-981-19-3998-3_70" @default.
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