A port water navigation solution based on priority sampling SAC: Taking Yantai port environment as an example

Abstract

Navigating port waters is challenging due to obstacles and regulated buoys, making traditional algorithms insufficient. Maritime Autonomous Surface Ships (MASS) must comply with strict International Association of Marine Aids and Lighthouse Authorities (IALA) regulations. This study presents an innovative navigation system integrated into an intelligent research ship, utilizing a Soft Actor-Critic (SAC) approach for decision-making. We train a navigation model in a custom Unity3D simulation that includes the IALA buoy system, employing a novel prioritization method to improve sample efficiency. Results show effective navigation in simulated environments, validated by real-ship testing at Yantai Port. This research enhances port navigation strategies and promotes the intellectualization of maritime operations by improving onboard decision-making and information processing.