The Earth's oceans, covering over 70% of the planet's surface, represent a vast frontier for scientific discovery and resource utilization, yet remain largely unexplored. This is due in large part to the formidable challenges the marine environment presents, including complex and unpredictable currents, pervasive turbulence, and extreme hydrostatic pressures. Conversely, millions of years of evolution have endowed aquatic organisms with remarkably efficient and versatile locomotion mechanisms to navigate these very conditions. These biological systems demonstrate superior performance in terms of speed, agility, and stealth. The underlying principles of locomotion, sensing, and neural control found in these creatures offer a rich source of inspiration for developing the next generation of underwater robots. While recent years have witnessed significant progress in applying underwater bio-inspired robots to tasks like deep-sea exploration and environmental monitoring, a substantial performance gap persists between engineered systems and their natural counterparts, motivating continued and focused research.
Addressing the growing demand for advanced capabilities in applications such as deep-sea exploration, long-range persistent monitoring, and ecologically sensitive surveillance requires a paradigm shift in traditional underwater vehicle design. This research topic seeks to convene leading research at the intersection of biology, materials science, and robotics to accelerate the development of high-performance, bio-inspired underwater systems. By integrating insights from nature with breakthroughs in areas like soft robotics, smart materials, and artificial intelligence, we aim to push the boundaries of aquatic robot performance. This collection will highlight novel research that enhances key metrics, including but not limited to: propulsive efficiency, speed, maneuverability, stealth (acoustic and visual), environmental sensing, and operational autonomy. We aim to foster a comprehensive dialogue on creating robots that are not only more capable but also more harmonious with the aquatic environments they explore.
We encourage submissions that present novel theoretical frameworks, computational models, and experimental validations related to bio-inspired underwater robotics. Submissions are invited on, but not limited to, the following topics:
(1) Novel Mechatronic Design: Innovations in soft and compliant mechanisms, smart materials and structures (e.g., shape-memory alloys, dielectric elastomers), and variable stiffness systems.
(2) Hydrodynamic Modeling and Simulation: Advanced analytical, numerical, and data-driven methods for modeling the complex fluid-structure interactions.
(3) Sensing and Perception: Development of novel underwater sensing modalities inspired by biological systems, such as artificial lateral lines, bio-inspired vision and sonar, and multisensory fusion.
(4) Control Systems and Autonomy: Model-based, model-free, and learning-based (e.g., reinforcement learning) control strategies for achieving high-performance locomotion, maneuverability, and autonomous decision-making.
(5) Bio-robotic Interaction: Studies on the dynamic interactions between bio-inspired robots and living aquatic organisms.
(6) System Integration and Field Deployment: Papers detailing the complete design, integration, and deployment of bio-inspired underwater systems in field environments.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
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Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.