Secrets of Highly Efficient Swimming Uncovered for Design of Next-Generation Underwater Drones
Unlocking Efficient Underwater Travel: University of Virginia researchers uncover the secrets of adaptable swimming speeds, revolutionizing the design of next-generation underwater drones.
Traditional underwater vehicles are limited to specific cruising speeds, lacking the versatility seen in fish swimming at varying speeds. Imagine the need for underwater vehicles to swiftly traverse vast ocean distances, then slow down for precise mapping of a narrow coral reef, or accelerate to reach an oil spill site while maintaining accuracy in measurements.
Dan Quinn
To tackle this challenge, Assistant Professor Dan Quinn and postdoctoral researcher Qiang Zhong from the University of Virginia School of Engineering and Applied Science have developed a fundamental approach to enable multi-speed missions. Their findings, published in Science Robotics, present a simple yet groundbreaking method applicable to underwater vehicle design.
Determining the optimal stiffness of the propelling element in swimming robots has long been a complex question for scientists. The same level of rigidity that performs well in certain scenarios may fail in others.
Quinn compares the rigidity issue to having only one gear ratio on a bicycle. It would be efficient only at one speed, akin to riding a fixed-gear bike through hilly San Francisco, resulting in exhaustion after a short distance.
Fish, on the other hand, appear to solve this dilemma by dynamically adjusting their stiffness in response to different circumstances. However, measuring the stiffness of swimming fish is challenging, making it difficult to understand their methods. To address this, Quinn and Zhong combined fluid dynamics, biomechanics, and robotics to derive a model for tail stiffness and its tunability.
Tunable Stiffness Unlocks Versatile Speeds and Enhanced Energy Efficiency in Fish-Like Robots
Their mathematical analysis yielded a remarkably simple result: stiffness should increase with the square of swimming speed. To validate their concept, they built a fish-like robot equipped with a programmable artificial tendon to adjust tail stiffness while swimming in a water channel. The outcome was remarkable— the robot exhibited a broader range of speeds while consuming nearly half the energy compared to a robot with a fixed-stiffness tail.
Zhong emphasized that their work is the first to comprehensively study tail stiffness by integrating biomechanics, fluid dynamics, and robotics. Their approach not only sheds light on the long-standing mystery of how tail stiffness impacts swimming efficiency but also provides a practical guideline for implementing tunable stiffness. In realistic swimming missions, the proposed tunable stiffness technique demonstrated high-speed and high-efficiency swimming.
With the benefits of tunable stiffness modeled, the team aims to extend their approach to other swimming styles. While the initial robot design mimicked a tuna, they plan to explore scaling up to dolphins or down to tadpoles. Additionally, they are developing a robot capable of replicating the undulating movements of stingrays.
Quinn expressed that the team’s endeavors are far from over, as every marine creature they study inspires new insights for the advancement of swimming robots. With countless fish species yet to be explored, the possibilities for innovation are vast.
Originally published by scitechdaily.com
Reference: “Tunable stiffness enables fast and efficient swimming in fish-like robots” by Q. Zhong, J. Zhu, F. E. Fish, S. J. Kerr, A. M. Downs, H. Bart-Smith and D. B. Quinn, 11 August 2021, Science Robotics.
DOI: 10.1126/scirobotics.abe4088
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