Advances in Intelligent Coordination Control for Autonomous UUVs

Dear Colleagues,

In recent years, intelligent coordination control for autonomous underwater unmanned vehicles (AUUVs) has garnered increasing attention due to their vast potential across various fields, including environmental surveillance, disaster monitoring, underwater exploration, logistics, and pipeline maintenance. These autonomous systems, often working cooperatively with multiple vehicles, require advanced control mechanisms to ensure efficient operation, broad coverage, and robust performance, particularly in dynamic and unpredictable environments. AUUVs must coordinate their motions in real time, frequently without human intervention, which demands sophisticated decision-making frameworks. The incorporation of advanced technologies like game theory, optimization algorithms, and machine learning has been pivotal in advancing these systems. Game theory enhances strategic interaction between vehicles, optimization techniques improve resource allocation and decision-making, and machine learning allows systems to learn and enhance performance from past experiences. Collectively, these technologies enable more robust, adaptive, and real-time control of AUUV operations. This research area is vital for the future of autonomous systems, addressing key challenges such as ensuring operational safety and optimizing system performance. These innovations will be instrumental in realizing the full potential of AUUVs across a wide range of industries.

This Special Issue aims to explore advanced coordination control strategies and intelligent decision-making mechanisms for AUUVs. The focus will be on leveraging machine learning, game theory, and optimization techniques to enable highly efficient and adaptive multi-agent coordination in dynamic underwater environments. Additionally, the issue will examine the interplay between model-based and data-driven approaches to enhance decision-making processes, facilitating real-time adaptability and system optimization. Lastly, the development of innovative control algorithms will be emphasized, ensuring improved operational safety, coordination precision, and intelligence in various applications, including environmental monitoring, logistics, and autonomous underwater exploration.

This Special Issue will welcome manuscripts that link the following themes:

• Different Applications of the Coordination Control of AUUVs.
• Intelligent Decision-Making, Planning, and Navigation Coordination Control of AUUVs.
• Distributed Optimization and Data-Driven Coordination Control of the AUUVs.
• Learning-Based Coordination Control of the AUUVs.
• Heterogeneous and Cross-Domain Coordination Control of the AUUVs.
• Anti-Disturbance and Resilient Coordination Control for AUUVs.
• Fault-Tolerance Coordination Control and Application of AUUVs.
• Safety-Based and Pravicy-Based Coordination Control of AUUVs.
• System Identification and Model-Based Coordination Control of AUUVs.

We look forward to receiving your original research articles and reviews.

Prof. Dr. Haitao Zhang
Dr. Bin-Bin Hu
Dr. Zhenghong Jin
Dr. Mingkang Long
Dr. Henglai Wei
Guest Editors

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• cooperative control
• autonomous underwater unmanned vehicles
• decision making
• game theory
• machine learning
• control theory
• distributed optimization
• intelligent connected vehicles
• vehicle dynamics control