论文标题
卫星导航和协调有限的信息共享
Satellite Navigation and Coordination with Limited Information Sharing
论文作者
论文摘要
我们探索空间交通管理，作为在车辆观察和通信范围有限的多代理系统中无冲动导航的应用。我们研究了在地面环境中训练在空间环境的碰撞多代理增强碰撞多代理增强型（MARL）模型的有效性。我们证明，转移学习模型优于直接在空间环境上训练的模型。此外，我们发现，即使我们考虑了由地球填充性引起的卫星动力学的扰动，我们的方法也可以很好地工作。最后，我们展示了如何使用我们的方法来评估卫星操作员之间信息共享的好处，以改善协调。
We explore space traffic management as an application of collision-free navigation in multi-agent systems where vehicles have limited observation and communication ranges. We investigate the effectiveness of transferring a collision avoidance multi-agent reinforcement (MARL) model trained on a ground environment to a space one. We demonstrate that the transfer learning model outperforms a model that is trained directly on the space environment. Furthermore, we find that our approach works well even when we consider the perturbations to satellite dynamics caused by the Earth's oblateness. Finally, we show how our methods can be used to evaluate the benefits of information-sharing between satellite operators in order to improve coordination.
