Path Planning Algorithms for AUVs Under Ocean Current Interference: A Survey of Disturbance Mitigation and Exploitation Strategies

Ocean current interference is a critical factor affecting the path planning of autonomous underwater vehicles (AUV). In ocean current environments, conventional path planning algorithms often exhibit significant limitations in complex flow fields without proper consideration of current interference. Therefore, to connect theoretical modeling with practical deployment while providing a systematic reference for developing current-resilient navigation strategies, this paper provides a comprehensive review of both environment modeling and algorithm evolution. Specifically, this survey first analyzes the impact of ocean current interference on AUV path planning and elaborates on the unique challenges arising in current-laden scenarios; it then reviews three categories of ocean current modeling methods (physics-based, historical-data-based, and real-time-observation-based approaches) in terms of their principles, advantages, limitations, and applicable scenarios; it next examines four mainstream categories of AUV path planning algorithms such as conventional graph-based methods, bio-inspired methods, intelligent learning-based methods and mathematical optimization under ocean current interference, where core improvement strategies and representative research achievements of each category are elaborated in detail; typical algorithms selected from these mainstream categories are then tested on a unified platform, and a comparative analysis of the results is presented; finally, current technical challenges and future research directions are summarized and discussed.