Abstract
In this paper, according to the requirements of intelligent task planning for multi missions such as cluster communication, collaborative observation and group manipulation, task planning is divided into task planning and action planning. On the basis of game theory and multi-objective optimization, artificial intelligence methods such as deep reinforcement learning, multi-agent game and group intelligent decision-making are introduced, the intelligent task planning method for multi spacecraft cluster is innovated and developed. The theoretical method of knowledge and data collaboration driven group intelligent game optimization hybrid task planning is proposed. The theoretical framework is constructed from the two levels of architecture level collaboration and algorithm level collaboration, which can provide theoretical and methodological reference for the follow-up intelligent task planning.
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