Dynamics, Control, and Design of Bionic Underwater Vehicles

Dear Colleagues,

Bionic underwater vehicles (BUVs), which draw inspiration from the morphological, locomotion, and sensory adaptations of aquatic organisms, represent a significant development in marine robotics. These systems offer the potential to achieve superior maneuverability, efficiency, and environmental compatibility compared to conventional designs, with applications spanning ecological monitoring to underwater infrastructure inspection. However, the development of performant and reliable BUVs is impeded by fundamental interdisciplinary challenges. The core difficulties lie in the tight coupling between bio-inspired mechanical design, the complex fluid–structure interactions governing their dynamics, and the synthesis of effective control strategies under significant hydrodynamic uncertainties. Progress in this field necessitates advances in high-fidelity modeling, robust control architectures, and the holistic integration of design and autonomy.

This Special Issue aims to present a collection of research that addresses these critical issues. We encourage contributions that advance the theoretical foundations, computational methods, and experimental validation of BUVs, pushing the boundaries of their capabilities and practical applicability. Topics of interest for this Special Issue include, but are not limited to, the following:

• Energy systems and harvesting technologies;
• Bio-inspired propulsion mechanism design and modeling;
• Novel actuation systems and smart material applications;
• Nonlinear dynamics and fluid–structure interaction analysis;
• Robust and adaptive control strategies;
• Bio-inspired control architectures and central pattern generators;
• Morphological design and multidisciplinary optimization;
• Biomimetic sensing and perception systems;
• Autonomous navigation and decision-making in uncertain environments;
• Multi-vehicle cooperation and swarm intelligence.

We welcome the submission of original research articles and comprehensive reviews that offer novel insights and substantiated results. Contributions that provide open-source datasets, models, or benchmark problems for the community are particularly encouraged.

Prof. Dr. Yilin Qu
Prof. Dr. Hongsheng Dong
Prof. Dr. Fuwang Zhao
Prof. Dr. Denghui Qin
Guest Editors

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