An enhanced APF algorithm for complex obstacles and COLREGs in maritime navigation

Abstract

This research addresses the significant limitations of current environmental potential field (EPF) methods in maritime navigation, particularly the oversimplification of obstacles represented by basic geometric shapes, which leads to navigational inaccuracies. We propose an enhanced artificial potential field (APF) algorithm capable of handling arbitrarily shaped obstacles, thus improving the realism and efficiency of path planning. By incorporating multiple repulsive force components when calculating forces from target ships, the International Regulations for Preventing Collisions at Sea (COLREGs) is integrated into the algorithm,ensuring compliance with maritime collision avoidance rules, enhancing the applicability of algorithm in real-world scenarios. Additionally, we develop advanced techniques for processing Automatic Identification System (AIS) data, including the identification of dense navigation areas and the removal of anomalous tracks, which improves data quality and reliability. Experimental setup utilizes real AIS data collected from commercial shipping routes under various environmental conditions, providing a robust foundation for validating the proposed methods. The experiments assess the algorithm’s capabilities in both global path planning and local collision avoidance. The results indicate that the enhanced APF algorithm generates realistic navigational paths that account for complex, irregularly shaped obstacles while adhering to COLREGs.