论文标题
基于近端政策优化算法的敏捷卫星的任务时间表
Mission schedule of agile satellites based on Proximal Policy Optimization Algorithm
论文作者
论文摘要
卫星的任务时间表如今是太空操作的重要组成部分，因为轨道上的卫星数量和类型正在大大增加，并且它们相应的任务也变得越来越复杂。在本文中，提出了与近端策略优化算法（PPO）相结合的任务时间表模型。与传统的启发式计划方法不同，本文将增强算法学习到其中，并找到一种描述问题的新方法。本文考虑了包括数据下载在内的几个约束。
Mission schedule of satellites is an important part of space operation nowadays, since the number and types of satellites in orbit are increasing tremendously and their corresponding tasks are also becoming more and more complicated. In this paper, a mission schedule model combined with Proximal Policy Optimization Algorithm(PPO) is proposed. Different from the traditional heuristic planning method, this paper incorporate reinforcement learning algorithms into it and find a new way to describe the problem. Several constraints including data download are considered in this paper.
