A model created by University of Virginia School of Engineering researchers that combines robotics, fluid dynamics and biomechanics has revealed the secret of stiffness tuning and allowed a fishlike robot to swim much more efficiently than a fish without a tunable tail.

Robotic fish tail could pave way for next-gen underwater drone design

Image credit: Dan Quinn and Qiang Zhong

Researchers in the US have demonstrated a technique for implementing varying cruise speeds in swimming robots, a discovery that could improve future designs of underwater vehicles.

Underwater vehicles are typically designed to have a single cruise speed, and they’re often inefficient at other speeds. The technology is rudimentary compared to the way fish swim, but researchers believe they have discovered a way of making underwater vehicles travel fast through miles of ocean, then slow down to map a narrow coral reef, or speed to the site of an oil spill then throttle back to take careful measurements.

Researchers at the University of Virginia’s (UVA) School of Engineering & Applied Science have developed a strategy for enabling these kinds of multispeed missions. They have shown a simple way to implement this strategy in robots that they believe could inform the design of future underwater vehicles.

When designing swimming robots, a question that keeps coming up is how stiff the piece that propels the robots through the water should be. This challenge emerges frequently, because the same stiffness that works well in some situations can fail miserably in others, according to experts.

“Having one tail stiffness is like having one gear ratio on a bike,” said Dan Quinn, an assistant professor at UVA. “You’d only be efficient at one speed. It would be like biking through San Francisco with a fixed-gear bike; you’d be exhausted after just a few blocks.”

According to the researchers, it is likely that fish solve this problem by tuning their stiffness in real-time: they 'dial-in' different levels of stiffness depending on the situation. Previously, there was no way for experts to measure the stiffness of a swimming fish, so it was hard to know if and how fish were doing this.

But Quinn and his colleague, recent UVA PhD graduate and postdoctoral researcher Qiang Zhong, have solved this by combining fluid dynamics and biomechanics to derive a model for how and why tail stiffness should be tuned. “Surprisingly,” Quinn said, “a simple result came out of all the math: Stiffness should increase with swimming speed squared.”

Assistant professor Dan Quinn, right, and postdoctoral researcher Qiang Zhong with the robotic tuna they designed to have a tail with tunable stiffness.

Assistant professor Dan Quinn (on right) and postdoctoral researcher Qiang Zhong with the robotic tuna they designed to have a tail with tuneable stiffness.

Image credit: University of Virginia School of Engineering and Applied Science

To test their theory, the researchers built a fishlike robot that uses a programmable artificial tendon to tune its own tail stiffness while swimming in a water channel. “Suddenly our robot could swim over a wider range of speeds while using almost half as much energy as the same robot with a fixed-stiffness tail,” Quinn observed. “The improvement was really quite remarkable.”

Zhong added: “Our work is the first that combines biomechanics, fluid dynamics, and robotics to study tail stiffness, which helps to uncover the long-existing mystery about how tail stiffness affects swimming performance.

“What is even more fantastic is that we are not just focused on theory analysis, but also on proposing a practical guide for tuneable stiffness. Our proposed tuneable stiffness strategy has proved effective in realistic swimming missions, where a robot fish achieved high speed and high-efficiency swimming simultaneously.”

The research team next plan to extend their model to other kinds of swimming. The first robot was designed like tuna; now the team is thinking about how they could scale up to dolphins or down to tadpoles. They’re also building a robot that emulates the undulatory motions of stingrays.

“I don’t think we’ll run out of projects anytime soon,” Quinn explained. “Every aquatic animal we’ve looked at has given us new ideas about how to build better swimming robots. And there are plenty more fish in the sea.”

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