Multi-AUV cooperative control and autonomous obstacle avoidance study

In response to the intricate marine environment and the need for diverse, intelligent, and large-scale operations, clustered Autonomous Underwater Vehicles (AUVs) have emerged as a pivotal trend in AUV oceanic applications. This paper delves into three key aspects of clustered AUV control: optimal formation assembly, dynamic cooperative control, and autonomous obstacle avoidance. The formation assembly is approached as a target point allocation problem, employing an F-Norm and Dubins Path (FNDP) based method for efficient path planning and optimal allocation. A novel hybrid control strategy, LFVS, combines leader–follower (LF) and virtual structure (VS) approaches, facilitating cohesive formation maintenance with minimal communication. Additionally, the paper introduces an intelligent adaptive artificial potential field (IA2PF) method. This technique, enhancing energy efficiency and obstacle avoidance, dynamically adjusts to current conditions, thereby overcoming limitations of traditional APF methods like unreachable targets , oscillation, and dead zones. The efficacy and applicability of these methods are corroborated through extensive simulations and practical experiments using three 260 AUVs, and compared with formation control based on the LF strategy, proving their utility and stability in real-world formation assembly and maintenance tasks.