This work focuses on the main challenges and problems in developing a virtual
oceanic environment reproducing real experiments using Unmanned Surface
Vehicles (USV) digital twins. We introduce the key features for building
virtual worlds, considering using Reinforcement Learning (RL) agents for
autonomous navigation and control. With this in mind, the main problems concern
the definition of the simulation equations (physics and mathematics), their
effective implementation, and how to include strategies for simulated control
and perception (sensors) to be used with RL. We present the modeling,
implementation steps, and challenges required to create a functional digital
twin based on a real robotic sailing vessel. The application is immediate for
developing navigation algorithms based on RL to be applied on real boats.

本研究侧重于以无人表面船舶 (UAV) 数字孪生技术开发真实实验的虚拟海洋环境所面临的主要挑战和问题，介绍了构建虚拟世界的关键特征，并考虑使用强化学习代理进行自主导航和控制，以及如何在模拟控制和感知策略方面使用强化学习的真正实施问题。我们提出了基于真实航行机器人船只的功能数字孪生建模、实施步骤和挑战，该应用对基于强化学习的导航算法的实际船只应用具有即时的指导作用。