Engineers at Caltech, ETH Zurich, and Harvard are developing an AI system that enables remotely operated vehicles (ROVs) to use ocean currents to aid their navigation. This system, powered by reinforcement learning (RL) networks, allows ROVs to make decisions about how to move for themselves, making navigation more efficient and enabling longer exploration missions in difficult environments.
Navigating Ocean Currents with AI
Traditionally, ROVs have relied on human operators to control their movements, which can be a challenging and time-consuming task, especially in complex ocean environments. The new AI system aims to change that by empowering the ROVs to make their own decisions about how to navigate.
The Power of Reinforcement Learning
The key to this system is the use of reinforcement learning (RL) networks. RL allows the AI system to learn from its experiences, gradually improving its decision-making abilities over time. As the ROV navigates through the currents, the RL network observes the results of its actions and adjusts its behavior accordingly, becoming more efficient and effective at using the ocean’s natural currents to its advantage.
Enabling Longer Exploration Missions
By allowing ROVs to make their own navigation decisions, the AI system can significantly reduce the time and effort required to control the vehicles remotely. This, in turn, enables ROVs to undertake longer exploration missions in challenging environments, where they can gather valuable data and insights that would otherwise be difficult or impossible to obtain.